Supporting medication-related decision making with ...

Supporting medication-related decision making with information model-based digital

documents

Thesis submitted in fulfilment of the requirements for the award of the degree of Doctor of Philosophy

Submitted: March 2007

Jean-Pierre Calabretto

B.Pharm. (South Australian Institute of Technology)M.Comput.St. (Deakin University)

School of Computer and Information Science,Division of Information Technology, Engineering and the Environment,

University of South Australia

Table of contents

Table of contents i

List of Figures ix

List of Tables xi

List of Publications xiii

Glossary xiv

Abstract xvi

Declaration xviii

Acknowledgements xix

Chapter 1 The challenges of the health care system: an introduction 1

1.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.2. The health of the health care system . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.3. Medication and chronic illness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.3.1. Adherence to medication therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.3.2. Medications and patient safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.4. The promise of information technology in Health . . . . . . . . . . . . . . . . 81.4.1. Electronic health records . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101.4.2. Decision support systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

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1.4.3. Mobile health applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

1.5. The problems of information technology in Health . . . . . . . . . . . . . . 141.5.1. Information and context of use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141.5.2. knowledge use by health professionals. . . . . . . . . . . . . . . . . . . . . . . . . . . . 151.5.3. Electronic health records . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151.5.4. Decision support, alerts and reminders . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161.5.5. Mobile computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171.5.6. privacy & security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181.5.7. The bottom line with IT in Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

1.6. Medication management and pharmacists. . . . . . . . . . . . . . . . . . . . . 20

1.7. The research problem. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

1.8. Scope of the research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

1.9. Significance and contributions of the research . . . . . . . . . . . . . . . . . 27

1.10. Outline of the thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Chapter 2 Addressing the problem of medication-related decision support for pharmacists: investigating the literature 31

2.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

2.2. Identifying appropriate medication management support for pharmacists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

2.2.1. Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322.2.2. Finding evidence in the literature. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322.2.3. Finding other evidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362.2.4. Was any evidence missed?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

2.3. Looking for a technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 412.3.1. Why a document? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432.3.2. What is a document?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

2.3.2.1. The historical perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .442.3.2.2. What is a digital document? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .442.3.2.3. Managing documents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .452.3.2.4. Genres . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .46

2.3.3. The expression of information in documents. . . . . . . . . . . . . . . . . . . . . . . . 472.3.4. Documents in communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 502.3.5. Workflow in Health. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

2.3.5.1. The flow of work in Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .522.3.6. Collaboration, Cooperation and Coordination . . . . . . . . . . . . . . . . . . . . . . . 542.3.7. Other advantages of documents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

2.3.7.1. Self awareness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .552.3.7.2. Social roles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .552.3.7.3. The paper-record as a work tool. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55

2.3.8. Wrapping up the document discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

2.4. Chapter summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

Chapter 3 Methodology 60

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3.1. Introduction and Research Framework. . . . . . . . . . . . . . . . . . . . . . . . 60

3.2. Research dimensions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 613.2.1. How the research was done . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 623.2.2. The purpose of the project. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 623.2.3. Ensuring relevance and rigour. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 633.2.4. Contribution to knowledge and theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 643.2.5. Contribution to practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

3.3. Overview of IS research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 653.3.1. Philosophical framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 653.3.2. The direction of theory. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 653.3.3. The research paradigm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 663.3.4. Prevailing paradigms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

3.3.4.1. Positivism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .673.3.4.2. Interpretivism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .683.3.4.3. Critical theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69

3.3.5. Methods of analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 693.3.6. Applicability of IS research approaches to the health environment. . . . . . . 71

3.4. Methods in IS research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 713.4.1. A taxonomy of research methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 713.4.2. Comparison of candidate research methods. . . . . . . . . . . . . . . . . . . . . . . . 73

3.4.2.1. Action Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .733.4.2.2. Ethnography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .743.4.2.3. Grounded theory. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .743.4.2.4. Case study research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .753.4.2.5. Design Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .75

3.4.3. Selection and justification of the research method . . . . . . . . . . . . . . . . . . . 77

3.5. Research Plan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 783.5.1. The hospital context (Part 1) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 793.5.2. The community context: prototype bench testing (Part 2A). . . . . . . . . . . . . 803.5.3. Medication review field study (Part 2B) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

3.6. Data collection techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 833.6.1. Quantitative and qualitative data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 833.6.2. Validity through triangulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 833.6.3. Data collection techniques. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

3.6.3.1. Literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .843.6.3.2. Use of questionnaires . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .843.6.3.3. Use of interviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .843.6.3.4. Work practice observation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .853.6.3.5. Use of focus groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .853.6.3.6. Documents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .863.6.3.7. Prototyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .86

3.7. Data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 873.7.1. Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 873.7.2. Prototyping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 883.7.3. Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 883.7.4. Content analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 883.7.5. Evaluation of research goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

3.8. Technology and Standards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 903.8.1. XForms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 903.8.2. The impact of standards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

3.8.2.1. CDA/HL7. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .913.8.3. User interface design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

3.9. Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

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3.10. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

Chapter 4 Design research in complex environments 95

4.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

4.2. Design – what’s in a name? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

4.3. Dealing with complexity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

4.4. Design research in education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100

4.5. Design research in information systems . . . . . . . . . . . . . . . . . . . . . 105

4.6. Designing a better health technology intervention . . . . . . . . . . . . . 108

4.7. Design research foundations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1114.7.1. The design research cycle. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1144.7.2. Design research outputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

4.8. Aligning the research plan and design research process . . . . . . . 118

4.9. Chapter summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121

Chapter 5 Formulating the information model: the hospital scenario 122

5.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122

5.2. The Data Gathering Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1235.2.1. Questionnaires and interviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1235.2.2. Work practice observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

5.2.2.1. Clinical pharmacy practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1255.2.2.2. The medication review process in the ward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .125

5.2.3. Documents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127

5.3. Analysis and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1285.3.1. Missing information and surrogate value. . . . . . . . . . . . . . . . . . . . . . . . . . 130

5.3.1.1. Missing Information relevant to Medical Officers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1315.3.1.2. Missing Information relevant to Pharmacists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1315.3.1.3. Pharmacist techniques for obtaining missing information. . . . . . . . . . . . . . . . . . . . . . . . . .1325.3.1.4. Medical Officers as a source of information for pharmacists . . . . . . . . . . . . . . . . . . . . . . .1335.3.1.5. Alternative information sources for MOs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1345.3.1.6. Work practice confirmation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1355.3.1.7. The implications of missing information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .136

5.3.2. Information granularity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1395.3.2.1. Information required by medical officers to initiate a medication order. . . . . . . . . . . . . . . .1395.3.2.2. Information used by pharmacists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1395.3.2.3. Observed information use by pharmacists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .140

5.3.3. Conversation and communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1425.3.3.1. Pharmacist communication with Medical Officers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1425.3.3.2. Communication with nursing professionals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1425.3.3.3. Other pharmacists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1435.3.3.4. Other health professionals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1435.3.3.5. Pharmacist conversations observed during work practice . . . . . . . . . . . . . . . . . . . . . . . . .143

5.3.4. Time constraints and summary information. . . . . . . . . . . . . . . . . . . . . . . . 1455.3.5. Decision support tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146

5.3.5.1. Decision support tools used by pharmacists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .146

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5.3.5.2. Pharmacists' understanding of decision support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1475.3.5.3. Decision support and Medical Officers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1475.3.5.4. Fitting decision support into work practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1475.3.5.5. Is decision support a realistic expectation? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1495.3.5.6. An ideal decision support tool?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1495.3.5.7. The acceptability of alerts and reminders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1515.3.5.8. The acceptance of blocking medication orders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .152

5.3.6. Complementary and Over-the-Counter medication. . . . . . . . . . . . . . . . . . 1535.3.7. Document analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154

5.4. Formulation of the information model . . . . . . . . . . . . . . . . . . . . . . . 156

5.5. The digital document . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1595.5.1. Some preliminary activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1595.5.2. Developing the digital document . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160

5.5.2.1. Patient details page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1615.5.2.2. Treatment information page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1645.5.2.3. Medication information page. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1655.5.2.4. Investigations page. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1685.5.2.5. Health Professional contacts page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .168

5.5.3. Experiences with XForms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169

5.6. Chapter summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170

Chapter 6 Modelling for the community context: benchtop testing 172

6.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172

6.2. The data gathering process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1736.2.1. Questionnaires and interviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1736.2.2. Prototype testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174

6.2.2.1. Accredited pharmacists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1746.2.2.2. The HMR process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .175

6.2.3. The focus group. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1766.2.4. Document analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176

6.3. Analysis and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1766.3.1. Missing information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178

6.3.1.1. Missing information for HMR pharmacists in GPs’ referrals . . . . . . . . . . . . . . . . . . . . . . . .1786.3.1.2. Pharmacists coping with missing information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1806.3.1.3. The implications of missing information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .181

6.3.2. Information granularity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1826.3.3. Conversation and communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1836.3.4. Time constraints and summary information. . . . . . . . . . . . . . . . . . . . . . . . 1836.3.5. Decision support tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184

6.3.5.1. Decision support tools used by pharmacists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1846.3.5.2. Pharmacists’ understanding of decision support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1846.3.5.3. Fitting decision support into work practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1856.3.5.4. Is decision support a realistic expectation? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1856.3.5.5. An ideal decision support tool. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .185

6.3.6. Systems for experts rather than expert systems . . . . . . . . . . . . . . . . . . . . 1866.3.7. A technology-poor practice paradigm. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1876.3.8. The ‘viewpoints’ of professional practice tools . . . . . . . . . . . . . . . . . . . . . 1886.3.9. Pharmacists’ perceptions of GPs in the HMR process . . . . . . . . . . . . . . . 1896.3.10. Prototype testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190

6.3.10.1. User reactions to the prototype. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1916.3.10.2. User suggestions for the prototype. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1916.3.10.3. User innovations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1926.3.10.4. Functional prototype issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .193

6.3.11. Document analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1946.3.11.1. Referral documents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1946.3.11.2. Reports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .195

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6.3.12. Opportunities for the digital document to improve HMR practice . . . . . . 1956.3.12.1. The medication management review process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1956.3.12.2. Opportunities to improve the patient outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .196

6.4. The community aligned information model. . . . . . . . . . . . . . . . . . . 196

6.5. The digital document and the server service . . . . . . . . . . . . . . . . . . 1996.5.1. The VB Browser . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1996.5.2. The digital document . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201

6.5.2.1. Patient details page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2046.5.2.2. Treatment details page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2066.5.2.3. Medication page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2076.5.2.4. Investigations page. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2106.5.2.5. Health Professional Contacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .210

6.5.3. The server service . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2116.5.3.1. Security. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2136.5.3.2. Server pages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2146.5.3.3. Summary of the technical changes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .220

6.6. Chapter summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221

Chapter 7 Evaluating the digital document: field studies 224

7.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224

7.2. The data gathering process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2257.2.1. Enrolling the participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2257.2.2. Data sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227

7.2.2.1. Field use of the digital document . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2277.2.2.2. HOMR testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2287.2.2.3. General Practitioner discussions and interviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2287.2.2.4. Patient-related data used for the trial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2287.2.2.5. Accredited pharmacists’ meetings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2297.2.2.6. Other conversations and meetings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2297.2.2.7. Logs of telephone calls and email communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2297.2.2.8. HMR pharmacists’ focus group. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .230

7.2.3. Issues encountered during data gathering . . . . . . . . . . . . . . . . . . . . . . . . 2307.2.3.1. Field studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2307.2.3.2. HOMR testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2317.2.3.3. Meetings with GPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2317.2.3.4. Patient-related data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2337.2.3.5. Email. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2357.2.3.6. The focus group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .235

7.3. Analysis and discussion of findings . . . . . . . . . . . . . . . . . . . . . . . . . 2357.3.1. Missing information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2367.3.2. Information granularity and the language of health professionals . . . . . . . 2437.3.3. Conversation and communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2457.3.4. Time constraints and summary information. . . . . . . . . . . . . . . . . . . . . . . . 2467.3.5. The use of alerts and reminders. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2477.3.6. Systems for experts rather than expert systems . . . . . . . . . . . . . . . . . . . . 2487.3.7. A technology-poor practice paradigm . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2497.3.8. The ‘viewpoints’ of professional practice tools . . . . . . . . . . . . . . . . . . . . . 2507.3.9. Pharmacists’ perceptions of GPs in the HMR process . . . . . . . . . . . . . . . 2537.3.10. The Practice nurse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2537.3.11. Complementary medicines and over-the-counter medication . . . . . . . . . 2547.3.12. Field study experiences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255

7.3.12.1. HMRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2557.3.12.2. HOMRs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2567.3.12.3. RMMRs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2577.3.12.4. The technically aware GP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .257

7.3.13. Evaluation of the intervention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2597.3.13.1. Evaluation of the technology aspects of system use . . . . . . . . . . . . . . . . . . . . . . . . . . . .260

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7.3.13.2. Evaluation of the human aspects of system use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .262

7.4. The information model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269

7.5. The digital document and the server service . . . . . . . . . . . . . . . . . . 2717.5.1. The VB Browser . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2717.5.2. The digital document . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2717.5.3. The XSL report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2737.5.4. The server service . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277

7.6. Chapter Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278

Chapter 8 Summary and conclusions 280

8.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280

8.2. Project summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280

8.3. Themes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2828.3.1. Missing information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2838.3.2. Information granularity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2848.3.3. Conversation and communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2858.3.4. Time constraints and summary information. . . . . . . . . . . . . . . . . . . . . . . . 2868.3.5. Alerts and reminders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2878.3.6. Decision support tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2888.3.7. Systems for experts rather than expert systems . . . . . . . . . . . . . . . . . . . . 2908.3.8. A technology-poor practice paradigm . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2918.3.9. The ‘viewpoints’ of professional practice tools . . . . . . . . . . . . . . . . . . . . . 2918.3.10. Complementary and Over-the-Counter medication. . . . . . . . . . . . . . . . . 2938.3.11. Pharmacists’ perceptions of GPs in the HMR process . . . . . . . . . . . . . . 2948.3.12. The role of the Practice Nurse. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294

8.4. The evolution of the information model . . . . . . . . . . . . . . . . . . . . . . 297

8.5. research questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299

8.6. Research contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3048.6.1. Contributions to theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3048.6.2. Contributions to practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305

8.7. Future work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3068.7.1. More extensive field trials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3068.7.2. A ‘working document’ for medication management in a hospital. . . . . . . . 3068.7.3. HMR referral generation by Practice Nurses. . . . . . . . . . . . . . . . . . . . . . . 3068.7.4. A digital document approach in an Aged Care Facility . . . . . . . . . . . . . . . 3068.7.5. A digital document approach for information exchange for

discharged hospital cardiac patients. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3078.7.6. A portable medication record. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3078.7.7. A digital document approach for patient groups with

extensive medication use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3078.7.8. A shared record with health consumers . . . . . . . . . . . . . . . . . . . . . . . . . . 3088.7.9. A shared record with other health professionals . . . . . . . . . . . . . . . . . . . . 3088.7.10. GP information behaviour with GP desktop systems . . . . . . . . . . . . . . . 308

References 309
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Appendices 328

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List of Figures


1-1 The medication management pathway (Stowasser, Allinson & O'Leary 2004) . . . . . . . . . 211-2 Patient care skills for pharmacists adapted from Gowan & Roller (2004). . . . . . . . . . . . . . 261-3 Relationship of chapters and appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30


2-1 Process and results for pharmacy decision support information sources. . . . . . . . . . . . . . 38


3-1 Research questions in relation to research phases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 823-2 The HOT fit model (Yusof, Paul & Stergioulas 2006) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90


4-1 The Design Research cycle (Vaishnavi & Kuechler 2005) . . . . . . . . . . . . . . . . . . . . . . . 1134-2 Design Research outputs (Purao 2002) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1174-3 Project iterative research cycle and outputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119


5-1 Hospital medication review process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1275-2 The information model from document analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1555-3 Missing information model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1575-4 The hospital information model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1585-5 Visual Basic document viewer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1605-6 Patient details page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1625-7 Edit patient details form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1635-8 New allergy form. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1645-9 Treatment information page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1645-10 Medication page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1655-11 Edit medication form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1665-12 New medication form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1665-13 Medication history . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1675-14 Edit social issues form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1675-15 Investigations page. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1685-16 Health professional contacts page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169


6-1 Home medication review process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1756-2 The community-aligned information model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1986-3 Visual Basic document viewer (version 2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1996-4 VB Medication Management Document Printer form . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2006-5 VB HTML output of the digital document . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2016-6 Referral details page. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2026-7 Referral details page – after the review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203

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6-8 New reason for referral form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2036-9 Extended reasons for referral form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2046-10 Patient details page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2056-11 New reason for referral form – falls. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2066-12 Medication page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2076-13 Edit immunisations form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2086-14 Medication history . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2096-15 Edit medications form – after review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2106-16 Pathways for the HMR digital document. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2126-17 Server service for medication management document. . . . . . . . . . . . . . . . . . . . . . . . . . 2136-18 Server options after log-in. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2146-19 Document viewer with a ‘blank page’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2156-20 Open patient document. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2166-21 The patient document displayed on the server . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2176-22 Print patient document from the server. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2186-23 HMR report output in new browser window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2196-24 Save patient file locally . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220


7-1 Modified Hot Fit model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2607-2 The final information model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2707-3 Digital document referral page prior to review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2727-4 Digital document referral page after review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2737-5 HTML output of document before the HMR review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2747-6 HTML output of document after review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2757-7 HTML report output – calculated values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276


8-1 Project themes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2828-2 The evolution of the information model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2988-3 Research questions in relation to research phases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299

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List of Tables


1-1 Health system challenges. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31-2 Unintended consequences of CPOE (Campbell et al. 2006) . . . . . . . . . . . . . . . . . . . . . . . 16


2-1 NEDST criteria for selection of publications of EDSS (National Electronic Decision Support Taskforce 2002) . . . . . . . . . . . . . . . . . . . . . . . . . . 33

2-2 Categorisation of types of EDSS by the NEDST (National Electronic Decision Support Taskforce 2002) . . . . . . . . . . . . . . . . . . . . . . . . . . 33

2-3 Pharmacy-related electronic decision support systems revealed in literature . . . . . . . . . . 352-4 Desirable features for the digital document . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57


3-1 Research approaches (Neuman 2003, p. 31). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 623-2 Common methods in IS research (Choudrie & Dwivedi 2005) . . . . . . . . . . . . . . . . . . . . . . 723-3 Qualitative measures for the HMR field test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82


4-1 Comparisons of natural science and design science enquiry (Lee 2000). . . . . . . . . . . . . . 974-2 Dimensions of DR in education, IS and health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1124-3 Design research criteria (Rossi & Sein 2003) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118


5-1 Technical appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1235-2 The distribution of hospital participants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1245-3 Data-related appendices. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1285-4 Questions posed to pharmacists and MOs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1295-5 Research themes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1305-6 Missing information experienced by pharmacists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1355-7 Missing information – interviews and observed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1365-8 Information sources used by pharmacists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1415-9 Conversations between pharmacists and other professionals . . . . . . . . . . . . . . . . . . . . . 144


6-1 Technical appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1736-2 Data-related appendices. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1776-3 Questions posed to HMR pharmacists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1776-4 Research themes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1786-5 Risk factors for adverse outcomes for patients taking medications . . . . . . . . . . . . . . . . . 1796-6 Workflow and technology use in the HMR process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1876-7 Pharmacists’ suggestions for changes to the digital document prototype . . . . . . . . . . . . 1926-8 User innovations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1926-9 Information elements added to the model for the community context . . . . . . . . . . . . . . . 197

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7-1 Technical appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2257-2 Summary of data sources from the field studies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2277-3 The digital document paths in the field studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2317-4 Summary of interaction with GPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2337-5 Patient data sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2347-6 Research themes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2367-7 Comparison of missing information in referral documents – referral information . . . . . . . 2377-8 Comparison of missing information in referral documents – personal information . . . . . . 2397-9 Comparison of missing information in referral documents – treatment information . . . . . 2407-10 Comparison of missing information in referral documents – medication information . . . 2417-11 Comparison of missing information in referral documents – laboratory information . . . . 2427-12 GP desktop reports used to provide HMR referral information . . . . . . . . . . . . . . . . . . . . 2517-13 Net benefit comments from GP4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2597-14 Technology aspects of the intervention – 1a. System quality . . . . . . . . . . . . . . . . . . . . . 2617-15 Technology aspects of the intervention – 1b. Information quality . . . . . . . . . . . . . . . . . . 2627-16 Human aspects of the intervention – 2a System use . . . . . . . . . . . . . . . . . . . . . . . . . . . 2637-17 Human aspects of the intervention – 2b. User satisfaction. . . . . . . . . . . . . . . . . . . . . . . 2647-18 Organisational aspects of the intervention – Structure . . . . . . . . . . . . . . . . . . . . . . . . . . 2657-19 Organisational aspects of the intervention – Environment . . . . . . . . . . . . . . . . . . . . . . . 2667-20 Net benefits of the intervention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267


8-1 The implications of project themes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295

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List of Publications

The following publications emerged from this research.

Submitted to the European Journal of Information Systems – Special Issue on: HIS Research, Revelations and Visions – after acceptance of peer reviewed abstract.Building systems for experts: designing digital documents to support medication management, Jean-Pierre Calabretto, Paula MC Swatman, School of Computer and Information Science, University of South Australia, Adelaide, SA, Australia

In Press

Towards a working document to support medication management, J-P Calabretto, PMC Swatman, British Computer Society Health Informatics Forum (HC2007), 19-21 March 2007, Harrogate, England

Peer Reviewed

Supporting a Medication Management Model with Digital Documents, Jean-Pierre Calabretto, Paula M C Swatman, Jim Warren, Proceedings of the Australasian Confer-ence on Information Sciences (ACIS 2006), December 2006, Adelaide, South Australia

XForms for the Support of Medication Management, Jean-Pierre Calabretto, Debdeep Banerjee, Jim Warren, Linda Bird, Poster Abstract (peer-reviewed), Proceedings of the American Medical Informatics Association Conference 2005, Austin, Texas

Pharmacy decision support – where is it? – a systematic literature review, Jean-Pierre Calabretto, Jim Warren, Linda Bird, International Journal of Pharmacy Practice, Vol. 13, No. 3, pp 1-7, September 2005

Missing Information for Decision Making in Medication Management, Jean-Pierre Calabretto, Jim Warren, Linda Bird, Proceedings of the Thirteenth National Health Informatics Conference, Melbourne, Australia, 31st July – 2nd August, 2005(cited by Bindoff et al. #)

Citations# Bindoff, IK, Tenni, PC, Peterson, GM, Kang, BH & Jackson, SL 2007, 'Development of an intelligent decision support system for medication review', Journal of Clinical Pharmacy and Therapeutics, vol. 32, no. 1, pp. 81-88.

Glossary

AACP . . . . . . . . . . . . . Australian Association of Accredited PharmacistsACF. . . . . . . . . . . . . . . Aged Care FacilityADE. . . . . . . . . . . . . . . Adverse Drug EventADR . . . . . . . . . . . . . . Adverse Drug ReactionADRAC . . . . . . . . . . . . Australian Drug Reactions Advisory Committee AE . . . . . . . . . . . . . . . . Adverse EventAMH . . . . . . . . . . . . . . Australian Medicines HandbookAR . . . . . . . . . . . . . . . . Action ResearchASP. . . . . . . . . . . . . . . Active Server PagesBMI . . . . . . . . . . . . . . . Body Mass IndexBP . . . . . . . . . . . . . . . . Blood pressureCCl . . . . . . . . . . . . . . . Creatinine ClearanceCDA . . . . . . . . . . . . . . Clinical Document ArchitectureCDSS . . . . . . . . . . . . . Clinical Decision Support SystemCIG . . . . . . . . . . . . . . . Computer Interpretable GuidelineCM . . . . . . . . . . . . . . . Complementary MedicineCoP . . . . . . . . . . . . . . . Communities of PracticeCPOE . . . . . . . . . . . . . Computer Physician Order EntryCS . . . . . . . . . . . . . . . . Computer ScienceCSCW . . . . . . . . . . . . . Computer-Supported Collaborative WorkCSS. . . . . . . . . . . . . . . Cascading Style SheetsDMMR. . . . . . . . . . . . . Domiciliary Medication Management ReviewDR. . . . . . . . . . . . . . . . Design ResearchDSS. . . . . . . . . . . . . . . Decision Support SystemDUE . . . . . . . . . . . . . . Drug Utilisation EvaluationE/DMS. . . . . . . . . . . . . Electronic/Document Management SystemEDM . . . . . . . . . . . . . . Electronic Document ManagementEDSS . . . . . . . . . . . . . Electronic Decision Support SystemEHR . . . . . . . . . . . . . . Electronic Health RecordEKP. . . . . . . . . . . . . . . Emergent Knowledge-intensive ProcessEP . . . . . . . . . . . . . . . . Electronic PrescribingGFR . . . . . . . . . . . . . . Glomerular Filtration RateGP. . . . . . . . . . . . . . . . General PractitionerHI . . . . . . . . . . . . . . . . Health Informatics HIC . . . . . . . . . . . . . . . Health Insurance CommissionHIS . . . . . . . . . . . . . . . Health Information SystemHL7 . . . . . . . . . . . . . . . Health Level 7HMR . . . . . . . . . . . . . . Home Medication Review HOMR . . . . . . . . . . . . . Hospital Outreach Medication Review HOT Fit . . . . . . . . . . . . Human-Organisation-Technology FitICU . . . . . . . . . . . . . . . Intensive Care UnitIE. . . . . . . . . . . . . . . . . Internet ExplorerIS. . . . . . . . . . . . . . . . . Information SystemsIT. . . . . . . . . . . . . . . . . Information TechnologyMD . . . . . . . . . . . . . . . Medical DirectorMIMS. . . . . . . . . . . . . . Monthly Index to Medical Specialities (monthly/annual)MM . . . . . . . . . . . . . . . Medication Management MO . . . . . . . . . . . . . . . Medical OfficerNEDST . . . . . . . . . . . . National Electronic Decision Support Task Force

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OTC . . . . . . . . . . . . . . Over-the-CounterPBS . . . . . . . . . . . . . . Pharmaceutical Benefits SchemePC . . . . . . . . . . . . . . . . Personal ComputerPDA. . . . . . . . . . . . . . . Personal Digital AssistantQoL . . . . . . . . . . . . . . . Quality of LifeQUM . . . . . . . . . . . . . . Quality Use of MedicinesRCF. . . . . . . . . . . . . . . Residential Care FacilitiesRDNS . . . . . . . . . . . . . Royal District Nursing ServiceRMMR. . . . . . . . . . . . . Residential Medication Management ReviewSHPA . . . . . . . . . . . . . Society of Hospital Pharmacists of AustraliaTAIS . . . . . . . . . . . . . . Therapeutic Advice and Information ServiceUK . . . . . . . . . . . . . . . . United KingdomUML . . . . . . . . . . . . . . Unified Modelling LanguageUniSA . . . . . . . . . . . . . University of South AustraliaUS . . . . . . . . . . . . . . . . United StatesVB . . . . . . . . . . . . . . . . Visual Basic

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Abstract

Medication is vital in treating chronic disease. Increasing use of medication, however, can lead to (potentially preventable) medication-related adverse events. Medication management offers a means of addressing such adverse events and pharmacists have an important role in this solution, especially in terms of reviews of patient medication.

Improved availability and sharing of patient-related information are critical factors in medication management, so that providing access to this information becomes a major factor in effective medication reviews. Although clinical decision support tools can significantly assist doctors in accessing relevant point-of-care information for greater patient safety, it has proven difficult to ensure the availability and appropriate structure of patient-related information for such support tools. These information access and input problems are further exacerbated by a lack of existing research into suitable decision support solutions for pharmacists.

This research project explored the suitability of an ‘essential’ information model to support an electronic document solution to support clinical documentation and allow effective communication between pharmacists and doctors for medication reviews. The project investigated whether this approach could improve safety, quality and efficiency in the medication review process; as well as more generally identifying factors influencing development and uptake of document-based support tools in the Health sector.

The project used a qualitative Design Research approach and iterated through three scenarios:

• The first, information-rich, hospital scenario developed an information model of essential medication management components, which underpinned the development of a digital document prototype – implemented using XForms technology

• in the second scenario, accredited pharmacists evaluated the digital document to enable refinement of the information model and its associated digital document for the broader ‘community’ context

• The third scenario involved field studies which evaluated the digital document (and thus the underlying information model) within the community, assessing its contribution to quality, safety and efficiency throughout the medication review process.

The investigation identified a number of themes which guided design and development of the prototype; and which appeared likely to have a broader impact on successful uptake of decision support tools.

Missing information proved to be a constant and serious problem for health professionals – although, in this project, it also became a way of determining the value of an information element and thus its inclusion in the information model. Conversation played a significant role in the hospital environment to help supply pharmacists’ information needs. Information granularity, the ‘language’ of health professionals; and their time constraints were major factors influencing design. Health professionals’ extensive use of their personal knowledge also suggested decision support tools in this sector should be ‘systems for experts’ rather than expert systems, i.e. the decision support tool and its user’s personal knowledge should complement one another.

The results of this proof-of-concept project suggest practice improvement in medication management is possible, with perceived improvements in safety, quality and efficiency of the

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medication management process. These benefits, however, now need to be affirmed in larger field studies.

The contributions of this research are two-fold: firstly, it is possible to develop a model of essential medication-related information which is succinct, relevant and can be understood and shared by health professionals – in conjunction with the individual’s personal knowledge. Secondly, a document metaphor is a natural fit with health professionals for representing and communicating information. Expressing this metaphor as digital document overcomes the main problems of paper-based documents – sharing and communication; and the dynamic properties of digital documents assist in decision-making.

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Declaration

I declare that:

this thesis presents work carried out by myself and does not incorporate without acknowledgment any material previously submitted for a degree or diploma in any university;

to the best of my knowledge it does not contain any materials previously published or written by another person except where due reference is made in the text; and all substantive contributions by others to the work presented, including jointly authored publications, is clearly acknowledged.

Jean-Pierre CalabrettoMarch 2007

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Acknowledgements

Foremost, I would like to thank my supervisor, Professor Paula Swatman for seeing me to completion of this thesis. Her generosity with time, advice and guidance, is unrivalled; and I am particularly grateful to her for the considerable effort she made to my supervision. In addition, her ability to accept a PhD student mid-way through their research project and keep this going smoothly is remarkable. I have valued her friendship and good humour during this time.

I thank the people who paved the way for my venture. Professor Jim Warren, who moved to Auckland, my first supervisor (now an Associate Supervisor), for his support and friendship in the first half of my project. Kingsley Coulthard, the Director of Pharmacy at the Women’s and Children’s Hospital, my colleague and friend for many years, whose unselfish support and encouragement I will remember.

For a mature-aged student, moving from full-time employment to full-time study can be daunting. As well as an Australian Postgraduate Award, I was very fortunate to receive support from the Distributed Systems Technology Centre (DSTC). For this, I thank Dr. Kerry Raymond, Mark Gibson and Jim Warren. I would also like to thank Dr. Linda Bird who was an Associate Supervisor for the life of the DSTC, and other staff of the DSTC (particularly Dr. Hoylen Sue) for their support and friendship. I also acknowledge the support of Professor Andy Koronios, the Head of the School of Computer and Information Science.

Of special note, is my rewarding association with the Australian Medicines Handbook; and especially thank Simone Rossi, Peter Farrell, Tony Loan, Lawrence Lim and Ceryle Gaehl.

There also many other academic and administrative staff (present and past) within the University that have facilitated my time as a student, offered advice, guidance and friendship. To these people I extend my gratitude. Professor Paul Swatman for his role during my change of supervisors; Associate Professor Carole Alcock, my Associate Supervisor; Roger Tagg; and Professor David Kearney. The administrative and support staff who are essential to smooth sailing within any organisation – Nicole Howard, Vicky Cini, Denise Manocchio, Marela Vuckov, Judy Pollock, Rita Jones, Lisa Brookling, Andrew Beveridge and Kate Pollitt. The IT support staff that allows work to occur – Malcolm Bowes, Steve Allen, Angelo Pace and Harry Sukamar. I acknowledge the help of David Gardiner, the many individuals from the University library and others who ran workshops that were invaluable in my pursuit of resources and necessary skills.

There is also an anonymous group of individuals who deserve some acknowledgement – the journal and conference reviewers who contributed to the betterment of my research writing.

Of course, the life of a research student would not be complete without the value and pleasure of interacting with other research students. These include my previous PhD chums Chunlan Ma, Sistine Barretto and Eric Browne with whom I had many meaningful conversations – and more recent student companions, particularly Nhiem Lu, Kuan Tan, Christian Voigt and David Raisey.

No research occurs without participants. Although they must remain anonymous, it would be remiss of me not to thank my participants. I am grateful for the generosity of the pharmacists, doctors and others who were part of my research. I would also like to thank the many other health professionals, particularly pharmacists, who were not directly part of my studies but supported me and contributed in other ways.

There is no way that I could have embarked on this venture without the love and support of my family – Helen my partner, my son Seb and my daughter Sophie. Despite the fact that Helen endured her own PhD, my family remained remarkably calm and supportive after I expressed my desire to do this. There is no doubt that a family will ‘keep it real’ and enables you to experience and share the things that are the most important in life. It is to Helen, Seb and Sophie; and to my father Lino who died in the month before I began this work, that I dedicate this thesis.

Chapter 1

The challenges of the health care system: anintroduction

1.1 Introduction

Health care should be safe, effective, patient-centred, timely, efficient, and equitable (Institute of Medicine 2001)

Using the Institute of Medicine’s goals for health care as starting points, this chapter introduces

the health system environment and the significant issues and challenges that face it. This

discussion carried out with both International and Australian perspectives, as although health

system structures may vary from country to country, the health care issues in Western

countries are common.

The chapter is structured as follows:

• the health system and the issues faced by it in Western countries are introduced in

Section 1.2

• the role of medication in the treatment of chronic disease and the subsequent concerns

with medication safety are discussed in Section 1.3

• Section 1.4 introduces the role and promise of using Information Technology (IT) in

health care and in particular, decision support

• the challenges to the use of IT and decision support in the health care domain are

discussed in Section 1.5

• the emerging and important role of pharmacists in medication management is discussed

in Section 1.6; and

• the research problem is disclosed Section 1.7

• the scope of the research is discussed in Section 1.8

• Section 1.9 explains the significance and contributions of the research project; and

• the thesis outline is described in Section 1.10

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1.2 The health of the health care systemGreenes (2001) suggests that it is not difficult to agree on some basic goals for achieving

quality in health care:

• universal health care coverage

• reduction of unnecessary variability and the adoption of best practices

• error reduction and safety

• increased patient-provider interaction and shared decision-making

• accountability of the health care system for cost-effectiveness

• protection of privacy; and

• more emphasis on disease prevention and health maintenance.

Yet, despite the ease with which any reader can see how important these goals are, the health

system is an exceptionally complex environment undergoing rapid change (both

organisationally and technologically); forced to cope with an aging population, the rapid growth

of new therapies and technologies and with the significant costs these new solutions bring with

them – and all of this set against a background of shrinking resources (National Health

Information Management Advisory Council 2001; Ortiz, Meyer & Burstin 2002).

There are some substantial challenges for the long-term sustainability of our health care

system (referred to as Health in this thesis), ranging from system-wide issues to those affecting

institutions and individuals. Table 1-1 presents a summary of some of these challenges,

compiled from: National Health Information Management Advisory Council (2001); European

Commission (2004); Southon (2003) and Greenes (2001).

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Southon (2003) believes that since no-one seems able to co-ordinate the conflicting

perspectives existing within Health, few of the major problems have effective solutions.

The problem is further complicated by the ‘epidemic’ of chronic disease affecting developed

and developing countries – related to dietary and lifestyle changes – responsible for 60% of

world deaths (World Health Organisation 2002). The shifting dietary patterns relate to the

increased consumption of energy-dense diets high in fat (particularly saturated fat), salt and

sugar (World Health Organisation 2002); together with the increased consumption of foods

that are low in unrefined carbohydrates (World Health Organisation 2003b). Of Australia’s 20.3

million people (as at June 2005), an estimated 2.5 million adults were obese – about 1 in 5

males aged 18 years; and 1 in 6 females. A further 4.9 million adults were estimated to be

overweight but not obese (Australian Institute of Health and Welfare 2006, p.15).

Table 1-1: Health system challenges

Challenge BackgroundAging The increasing proportion of older persons in the population.

Consumerism The increasing demand for; and changing expectations of consumers for health services.

New technologies The rapid increase and availability in the number of new services and products resulting from advances in research.

Financial return Difficulties experienced by public authorities in matching investment in technology with investment in complex organisational changes needed to exploit technology’s potential.

Mobility The increasing mobility of patients and health professionals within the health system.

Equity The continuing inequalities in health care and outcomes among disadvantaged groups.

Occupational issues The need to limit occupational accidents and diseases, to reinforce well-being at work and to address new forms of work-related diseases.

Emerging disease Responding to emerging disease risks (e.g. new communicable diseases such as Severe Acute Respiratory Syndrome).

Information management The management of enormous amounts of health information that need to be available securely, accessibly; and in a timely manner at the point of need.

Budgetary constraints The need to provide the best possible health care under limited budgetary conditions.

Workforce issues The increasing difficulty of maintaining a health workforce in light of many becoming alienated, retiring early, or moving to other careers.

Competition The increasing complexity of the system leading to the perception of competing stakeholders rather than cooperating partners.

Competing demands The difficulty of concurrently aiming for both quality and conservation of resources.

Lack of accountability The inability to measure what practices are effective without an overall system of accountability.

Information relevance The need for increased data collection (in part to achieve accountability) by practitioners that have little time or positive incentive to do so.

Time demands The time that is necessary to ensure quality may have negative effects on productivity – the primary basis for the current reward system.

Health professional-consumer relationships

Monitoring and accountability are among major irritants seen as interfering with physician liberties and the physician-patient relationship.

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Paradoxically, while one billion adults in the world are overweight and 300 million are clinically

obese in the more advantaged countries, poor countries have 170 million underweight

children, of whom over three million died in 2002 (World Health Organisation 2002).

Together with shifting dietary patterns, people in developed countries are experiencing a

decline in energy expenditure associated with a sedentary lifestyle resulting from motorised

transport, labour-saving devices, the phasing out of physically demanding manual tasks in the

workplace and leisure time largely devoted to physically undemanding pastimes (World Health

Organisation 2003b). In 2004, about half of Australia’s adults did not undertake leisure-time

physical activity at levels recommended for health benefits (Australian Institute of Health and

Welfare 2006, p.15).

As a result of these changes in diet and exercise, chronic non-communicable diseases (such

as obesity, diabetes mellitus, cardiovascular disease, hypertension and stroke; and some

types of cancer), are becoming increasingly significant causes of disability and premature

death, placing additional burdens on already overtaxed national health budgets (World Health

Organisation 2003b). In 2002, cardiovascular disease, cancer, chronic respiratory disease and

diabetes caused 29 million deaths worldwide (Yach et al. 2004). This pattern also exists in

Australia – the chronic diseases which contribute the most to morbidity, disability and mortality

are heart disease, stroke, cancer, diabetes, asthma and osteoarthritis. Some of these chronic

diseases are now considered to be of epidemic proportions (Australian Institute of Health and

Welfare 2006, p.76). For example, in 2004, cardiovascular disease accounted for 47,637

deaths (36% of all deaths) in Australia; and is also one of the leading causes of disability (about

1.4 million people). Cardiovascular disease is also the most expensive disease group in terms

of direct health care expenditure, at $5.5 billion – 11% of Australia’s total allocated health

system expenditure in 2000–01 (Australian Institute of Health and Welfare 2006, p.77). The

1999-2000 Australian Diabetes, Obesity and Lifestyle Study (AusDiab) indicated that 30% (or

3.7 million) of Australians aged 25 years or over had high systolic or diastolic blood pressure,

or were on medication for high blood pressure. The proportion of males and females with high

blood pressure also increases with age (Australian Institute of Health and Welfare 2006,

p.194).

The use of medication has become vital in the treatment of disease and medicines are now

part of most people's lives – especially for the elderly and chronically ill (Ihara, Summer &

Shirey 2002). This topic is examined next in Section 1.3.

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1.3 Medication and chronic illness An Australian report suggests that in any two-week period, about 7 in 10 Australians (and 9 in

10 older Australians) will have taken at least one medicine (Roughead & Semple 2002).

Medication alone was also the most common treatment given to patients by General

Practitioners (GPs), occurring on 37% of visits (at a rate of 101.5 prescriptions per 100

encounters or 69.8 prescriptions per 100 problems) – compared to clinical treatment alone

(e.g. counselling) on 11% of occasions (Australian Institute of Health and Welfare 2006,

p.365). The most commonly used drugs in Australia in 2004-05 were atorvastatin (used for

lowering blood cholesterol) followed by simvastatin (also for lowering blood cholesterol) and

ramipril (for treating chest pain and high blood pressure) (Australian Institute of Health and

Welfare 2006, p.365).

These figures relate only to prescription medications – but there is another group of

medications which contributes to this increasing trend of use. The Australian Institute of Health

and Welfare (2006) estimated that, in 2004, along with the 233 million prescriptions dispensed

in community pharmacies, Australians also spent $1.7 billion on Over-the-Counter (OTC)

medications such as analgesics, cough medicines and vitamins; and $0.8 billion on natural and

other Complementary Medications (CMs). The use of OTC and CM medications accounted for

over 14% of the recurrent Health expenditure in 2003-04 – taking medication to resolve

feelings of unwellness is a frequent health-related action taken by Australians.

1. 3.1 Adherence to medication therapyThe widespread use of medication has led to an increasing concern within the health

community about adherence to (prescription) medication regimens in the elderly and

chronically ill groups – adherence to long-term therapy for chronic illnesses in developed

countries averages about 50% (World Health Organisation 2003a).

The consequences of poor adherence to medication regimens for the chronically ill include:

poor health outcomes; poorer quality of life; and increased health care costs through such

factors as increased hospital emergency room visits, hospital admissions or visits to

community doctors (Ihara, Summer & Shirey 2002; World Health Organisation 2003a).

Conversely, good adherence to beneficial drug therapy has been associated with a decreased

risk of mortality (Simpson et al. 2006). Good adherence per se however, does not necessarily

constitute a good outcome, as good adherence to proved harmful drug therapy has been

shown to increase the risk of mortality (Simpson et al. 2006).

Osterberg and Blaschke (2005) have suggested some general approaches for improving

adherence to medication therapy, including: patient education, improved medication dosing

Page 5

schedules for patients, increased patient accessibility to doctors (i.e. shorter waiting times) and

better communication between doctors and patients. The study by Bajramovic, Emmerton and

Tett (2004) confirmed that information sharing between health professionals and consumers

was an important issue – not helped by the perceived lack of time in doctor-consumer

interactions; and the lack of systems to support good information-sharing. The authors of this

study went on to suggest that improvements in information sharing between doctors,

pharmacists and consumers were crucial to the future of health care (Bajramovic, Emmerton

& Tett 2004).

A further important issue is that much of the care needed in chronic illness involves a degree

of patient self-management which if not supported by the health system may leave patients at

risk (World Health Organisation 2003a). Increasing the ability of patients to self-manage (and

shifting the cost of medications more directly to the consumer) is also a motivation of many

governments. This motivation is reflected in the trend of making prescription medication

(including some for the prevention of serious illness) available Over-the-Counter (Cohen,

Paquette & Cairns 2005). This trend has implications for both the health care team and

patients themselves in terms of improving the safety of self-medication – the implications are

the need for better information for patients and more collaborative care involving better

communication between doctors, nurses and pharmacists (Bradley & Blenkinsopp 1996).

With the increasing involvement of patients in their own care, interventions by health

professionals (to improve patient adherence to medication therapy) are seen as positive

returns on investment – through the primary prevention of risk factors for medication therapy

and the secondary prevention of adverse health outcomes (World Health Organisation 2003a).

The increasing recognition of this fact is stated by the World Health Organisation:

Increasing the effectiveness of adherence interventions may have a far greater impact on the health of the population than any improvement in specific medical treatments (World Health Organisation 2003a)

The importance of adherence to medication therapy also raises the issue of medication safety.

The use of medicines is not without risks and this issue has been raised as an international

concern. The issue of medication-related adverse effects is discussed next in Subs-section

1.3.2.

1. 3.2 Medications and patient safetyThe landmark and widely quoted report To Err Is Human: Building a Safer Health System

(Kohn, Corrigan & Donaldson 1999) identified the extent and cost of preventable iatrogenic

injuries in the United States (US) hospital system – estimated to affect 3%-4% of US hospital

patients and account for over 7,000 deaths annually. The cost of dealing with preventable

Page 6

adverse drug events (ADEs) for US hospital inpatients was estimated to be about US $2 billion.

Similarly, findings from the United Kingdom (UK) suggested that inpatient medication errors

cost about £500 million a year (UK Audit Commission 2001).

Australian figures place medication-related hospital admissions at 2.5%, rising to 30% for

those patients aged over 75 – with up to three-quarters of these medication-related admissions

being potentially preventable. People aged over 65 years are considered to have higher rates

of medication incidents compared to younger people, as the elderly are taking more

medications (Roughead & Semple 2002). A review of high-risk individuals in the community

found 2.8 medication-related problems per person (Runciman et al. 2003). Other Australian

data suggest that of the 100 million or more annual general practice encounters in Australia,

about 400,000 are thought to involve medication-related adverse drug events (Roughead &

Semple 2002)

Roughead E.E. and Lexchin (2006) in an editorial in the Medical Journal of Australia,

commented that in light of more than 30 Australian studies estimating the number of ADEs in

a variety of settings: ’it is clear that counting is not enough — it is time for action’. Roughead

and Lexchin (2006) suggested that a way forward was through developing a ‘no blame’ culture

with better doctor-patient communication, better inter-health professional communication and

the use of technology. Some technology-based strategies which have been shown to reduce

medication incidents include: computerised prescribing with clinical decision-support,

information about medicines for health care providers on-line, or in prescribing or dispensing

software; and computerised adverse drug alerts (Roughead & Lexchin 2006).

Further, as the distinction between primary (community-based) and secondary (hospital-

based) care blurs, an urgent need exists to review medication management across the health

continuum (UK Audit Commission 2001).

The recognition of these-health related problems on a wide-spread scale has led to

government or national strategies to address these problems, many underpinned by IT. This

is discussed next in Section 1.4.

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1.4 The promise of information technology in HealthThe National Health Information Management Advisory Council (2001) suggested that

emerging priorities for governments included:

• maximising the health of individuals and the community

• achieving a balance in the investment of health resources in individual and community

health

• responding flexibly to community and consumer needs

• providing services that are integrated and coordinated

• relying on an evidence basis for health care to achieve best practice in health services;

and

• concentrating on proven services and on agreed priority areas

Alongside these priorities, there is an increasing recognition by governments of the importance

of increased and better use of health information. This includes: access to up-to-date health

information for both consumers and health providers; new and improved methods of

communicating information among and between consumers and health providers; the sharing

of information between consumers and health providers; and collecting, collating and

analysing information/data across health settings and populations (National Health Information

Management Advisory Council 2001).

However, the amount and complexity of health-related information and knowledge has

increased to such a degree that information processing in itself has become a major activity

for any health organisation (European Commission 2004). This overwhelming amount of

information makes it virtually impossible for individual health clinicians to provide high-quality,

error-free care on a consistent basis, since they are ‘inherently fallible information processors’;

and clinicians are supported by poor systems that allow errors to occur (Ortiz, Meyer & Burstin

2002). The problems of managing this 'explicit', increasingly evidence-based knowledge are

compounded by consideration of individuals’ 'tacit' knowledge which deals mainly with

experience; and the increasingly informed patient (Sowerby Centre for Health Informatics

2000).

To address the problems of this information-intensive health environment, governments

increasingly see IT as a valuable tool. IT promises substantial productivity gains, the ability to

cope with increasing demand on health care services, the ability to reshape the health care

delivery to make it more citizen-centred (European Commission 2004); and the ability to

address issues of quality and safety (Bates & Gawande 2003; Electronic Prescribing Initiative

2004). Safe care is now considered to require a degree of individualisation which would be

unimaginable without computerised decision support (Bates & Gawande 2003).

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The ubiquity of IT in health has given rise to the term e-Health: ‘the application of information

and communications technologies across the whole range of functions that affect the health

sector’ (European Commission 2004). This term is used to describe a wide range of

technology-based tools in Health such as: Internet-based applications; health information

networks; electronic health records; telemedicine services; personal wearable and portable

communicable systems; and health portals (European Commission 2004). The notion of e-

Health is that the ubiquity, flexibility and potential reach of the Internet will allow for the delivery

of high-quality, low-cost services (Sowerby Centre for Health Informatics 2000).

The main roles for IT in Health are seen to lie in: the management of information and

knowledge (Sowerby Centre for Health Informatics 2000); electronic prescribing (Electronic

Prescribing Initiative 2004); and clinical decision support (Bates & Gawande 2003). Decision

support tools – particularly, clinical practice guidelines, prescribing alerts and those providing

current patient information at the point of care – offer opportunities to reduce the numbers of

adverse events, unnecessary hospitalisations, reduce the duplication of diagnostic tests and

enhance decision-making for providers and consumers (thus increasing the quality of care and

health outcomes) (National Health Information Management Advisory Council 2001). Bates

and Gawande (2003) suggest that the types of tools able to prevent errors and adverse events

are those which can improve communication, make knowledge more readily accessible, assist

with calculations, perform checks in real time; and assist with monitoring. Although, many

areas of decision support activity have considerable overlap, the researcher will now provide

a brief introduction to some of the main areas of activity.

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1. 4.1 Electronic health recordsThe Australian National Electronic Health Records Taskforce (2000) defined an electronic

health record (EHR) as:

An electronic longitudinal collection of personal health information usually based on the individual, entered or accepted by health care providers, which can be distributed over a number of sites or aggregated at a particular source. The information is organised primarily to support continuing, efficient, and quality health care. The record is under the control of the consumer and is stored and transmitted securely (National Electronic Health Records Taskforce 2000, p. xv).

The advantages of EHRs seem very clear from this definition – again based on the report of

the same taskforce, they include:

• better consumer access to their own health information, thus allowing consumers to

make more informed decisions about their health care

• better provider access to information (with consumer consent) at the point of care

• fewer diagnostic tests (including the elimination of redundant tests)

• improved warnings and alerts to counter avoidable error (e.g. adverse drug interactions);

and

• better planned and co-ordinated care (including the capacity to develop comprehensive

care plans that providers and consumers alike would use)

EHRs are seen as fundamental to the ability of some electronic decision support tools to

function as the EHR will provide the source of patient data upon which many of these tools will

function (National Electronic Decision Support Taskforce 2002).

Substantial efforts to develop national shared EHR networks have been made by some

countries, including Brazil, Canada, England and Australia – the latter with a national project

named HealthConnect (Schloeffel 2004a). A major advance in the area of EHR design was the

Good European Health Record (GEHR) project – a large European Union-funded project

undertaken within eight European countries between 1992 and 1994 – which later evolved (in

2002) into the openEHR model (Schloeffel 2004b), which is based on archetypes1.

Other efforts in area of EHRs have ranged from those supporting specific patients groups such

as diabetics (Austin et al. 2003), community-based practices (Baron et al. 2005) and across

primary care and specialty practices in community networks (Poon et al. 2006).

1. 4.2 Decision support systemsAs previously mentioned, there is a great deal of overlap in what constitutes a decision support

system (DSS) so for this discussion the researcher will also include Computerised Physician

1. Archetypes define domain-specific concepts which can range from simple concepts such as ‘blood pressure’ or more complex concepts such as ‘family history’; and are important components for seman-tic interoperability.

Page 10

Order Entry (CPOE) or electronic prescribing (EP), as many alerting and reminder functions

(considered to be decision support) are part of CPOE systems.

There are also very many definitions for decision support systems. Clinical decision support

systems (CDSS) have been described as active knowledge systems which use two or more

items of patient data to generate case-specific advice, and are typically designed to integrate

a medical knowledge base, patient data and an inference engine to generate case specific

advice (OpenClinical 2004).

Although decision support is a key interest for this research project, it is well beyond the scope

of this thesis to discuss DSS in detail – rather, a synopsis of DSS follows. The properties of

decision support systems already described include:

• providing clinicians with access to relevant, evidence-based information at the point of

care (Delaney et al. 1999)

• comparisons of patient characteristics (with a credible knowledge base) that guide a

clinician by offering patient-specific and situation-specific advice (General Practice

Computing Group 1999; Eccles et al. 2002)

• providing access to laboratory test interpretations, calculation of drug dosages,

automated warnings and alerts, practice guidelines; and decision analysis (Remmlinger

2002)

• complex systems that can model the likelihood of future events and the effectiveness of

proposed interventions, based on individual patient data, the 'knowledge' of risks and the

effectiveness of interventions (Delaney et al. 1999)

• reminders, advice or interpretation specific to a given patient at a particular time (Wyatt

2000)

• use of active knowledge systems which use two or more items of patient data to

generate case-specific advice (Wyatt & Spiegelhalter 1991)

• access to electronically stored knowledge to aid patients, carers, and service providers in

making decisions on health care (National Electronic Decision Support Taskforce 2002).

Bates et al. (2003) summarised the features of DSS as supports which include passive and

active referential information as well as reminders, alerts, and guidelines. More generically,

decision support can describe any computer application which enhances a human's ability to

make decisions (Coiera 2003a).

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Examples of DSS from the literature are many and varied. Some include:

• guideline-based tools for emergency department clinicians (‘the asthma kiosk’, a patient-

driven decision-support tool which provides ED clinicians with tailored recommendations

for guideline-based treatment (Porter et al. 2006)

• a computer-assisted patient screening support for health care workers in India (Peters et

al. 2006)

• a hospital-based management of antimicrobial utilisation (McGregor et al. 2006); and

• the provision of on-line clinical decision-support information for health professionals

(Walther et al. 2002)

The importance given to electronic decision support in Australia was evidenced by the

establishment of the Australian National Electronic Decision Support Taskforce (NEDST). The

task of NEDST was to consider the benefits and difficulties electronic decision support and

recommend a way forward to ensure a consistent national approach to the development of

electronic decision support in Australia (National Electronic Decision Support Taskforce 2002).

A DSS can thus embody many definitions and exhibit a range of features – the considerable

overlap which results makes it very difficult to describe what a DSS ‘is’. Nevertheless, the

potential benefits that DSS offer to health care practice suggests an enduring quest to discover

what elements will afford effective decision support for health care professionals.

A significant feature of health care workers is their mobility which has in turn led to investigation

of the use of technology to support this mobile (nomadic) work. Mobile computing is discussed

in the next sub-section.

1. 4.3 Mobile health applicationsMobile computing is broadly described as computing technology – software, hardware and

communications – associated with mobility i.e. technology that is not fixed and is capable of

being portable (Hameed 2003). Examples of this technology include Personal Digital

Assistants (PDAs), laptop computers and mobile telephones. These mobile devices can also

include technology enabling users to communicate over a network, or directly with one other

using both wired and wireless technology (Hameed 2003).

The use of mobile technologies such as PDAs within hospital environments is not new

(Sargent et al. 2005) – applications based upon PDAs have included commercial medical or

drug references, medical calculators and personal organisation software, such as calendars

and address books (Barretta, Strayera & Schubarta 2004; Carroll & Christakis 2004). PDAs

are used less commonly for writing prescriptions or medical billing (Carroll & Christakis 2004).

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A study by Rothschild et al. (2006) demonstrated that PDA-based software (which included a

pharmacopoeia, an infectious disease reference, a medical diagnostic and therapeutic

reference; and transmitted medical alerts and other notifications during PDA-computer

synchronisations) was used frequently and improved patient care. Providing clinicians with up-

to-date drug-information alerts and warnings was considered especially valuable.

A promising area of use for mobile devices is remote access to information for primary health

care workers – as mobile portals for information access; and for the transmission of data from

remote locations to a central system (Hameed 2003). A challenge, however, for community

health services, is that many rely on legacy and paper-based systems (Sargent et al. 2005).

For the benefits of mobile devices to be fully realised requires the mapping of clinical pathways

to these devices so that they progress beyond the confines of traditional 'bricks and mortar'

hospital infrastructures – this non-trivial challenge should not be underestimated (Sargent et

al. 2005). An example of such an approach is the e-Therapeutics tools planned by the

Canadian Pharmacists Association (CPhA). These tools will combine evidence-based content

from CPhA, information from Health Canada (and others) and other applications (e.g. e-

prescribing, EHR) – this content will be delivered through multiple channels including a web

portal and be downloadable to a PDA (Canadian Pharmacists Association 2004a).

User acceptance of mobile devices is equally important. One way of achieving user

acceptance while simultaneously enhancing deliverability of the system – providing a ‘best fit’

with end user needs – is to address user concerns as they arise during development (Cooper,

Alcock & Burgess 2003). Cooper, Alcock and Burgess (2003) demonstrated this approach with

a proposed electronic point-of-care (ePOC) information system for ambulatory care services.

This system allowed the collection, delivery and exchange of timely information at point of care

to match complex health care workflow requirements, as well as allowing immediate updating

of health care records. The project enabled more timely and effective information access and

management – particularly, freeing up nurses from paper work and allowing more time for

consultation with patients (Cooper, Alcock & Burgess 2003).

Wireless technology has been used within a hospital environment with hand-held devices to

extend a clinical information system allowing improved information access and communication

at the point of care by providing: access to information resources, event monitoring and a

virtual whiteboard (Mendonca et al. 2004). Wireless technology can also be used to make

better use of clinicians’ time by allowing them to access the latest patient-related data when

they are located outside of a hospital campus (Holleran et al. 2003).

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1.5 The problems of information technology in HealthAlthough the benefits of IT in health care have been widely promoted, the health industry has

been a slow adopter of IT: estimates place IT expenditure in public health care at about 1.5%

of total revenue, which is significantly lower than that spent by other industries (e.g. banking

or the resources sector) (England 2001). The development of clinical DSS (CDSS) in health

care has, however, mirrored the general trend of IT adoption (Garg et al. 2005). The particular

problem of DSS uptake in Health is that tasks are often fuzzy, complicated and involves a great

number of people and technologies, whose activities are intricately linked – organisations

facing such tasks need high levels of information processing and exchange (Winthereik &

Vikkelsø 2005). A predicament is that existing patient care information systems often appear

to be based on formal, stepwise notions of health care work – these systems cannot handle all

potential exceptions and become impossible to maintain and to use (Ash, Berg & Coiera 2004),

so that failures of health information systems are common (Heeks 2006).

Some specific problem areas for IT in health care are now discussed in the following

subsections.

1. 5.1 Information and context of useThe health care environment is a paradox – characterised by an enormous amount of rapidly

changing information but at the same time hampered by the unavailability of critical information

at the point of clinical decision-making (National Electronic Decision Support Taskforce 2002).

For clinicians, the enormous amount of information they encounter in their job is a day-to-day

problem:

a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it (Varian 1995).

Consequently, information needs to be located, filtered and summarised – otherwise, the

technology which produces and distributes information is effectively useless (Varian 1995).

There is also a belief that, because of the overwhelming amount of information available to

clinicians, clinicians will intuitively understand the importance of problem-solving and learning

skills (such as how to find relevant answers quickly); and will see that clinical practice is not

simply about learning facts (Wyatt & Sullivan 2005). Unfortunately, however, this intuitive

understanding does not always take place.

Missing information in doctor-patient encounters is common and can affect both doctor-patient

interaction as well as clinical decision-making (Elder & Hickner 2005). The problem is further

complicated by the fact that information inaccuracies are common, for example:

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• incorrect recording of primary diagnosis for outpatient visits (57%) (Peabody et al. 2004)

• missing or uncoded medication data stored in electronic records (1.38 medications per

patient) (Wagner & Hogan 1996); and

• missing clinical information in primary care visits (13.6% of visits) (Smith et al. 2005)

In the last of these three studies, the authors noted that this missing clinical information had

the potential to adversely affect patients (44%), potentially resulting in delayed care or

additional services (59.5%); and added that significant time was spent unsuccessfully

searching for missing information (Smith et al. 2005). A recent study has shown that 51% of

hospital clinicians' information needs went unmet during their clinical practice; and that human

interaction was used to meet background information needs more frequently than was a

computer resource (Currie et al. 2003).

A critical feature of information is that it is contextual – its generation, use and value will depend

on the context of use (Shepherd et al. 2006) – specifically, the patient. Berg and Goorman

(1999) consider that information should be conceptualised as being always intertwined with the

context of its production – it is not simply a matter of using technology to transport information.

In addition, the further information has to circulate (i.e. the more diverse contexts in which it

must be usable), the more work is required to disentangle the information from its original

context (Berg & Goorman 1999).

1. 5.2 knowledge use by health professionalsAn important feature of Health is that health professionals need to access information from a

variety of sources. This access is not only to written material, but also involves other health

professionals – experts, specialists and consultants (Swatman et al. 1996). Thus, knowledge

in health care exists in a variety of modalities – tacit, explicit, experiential and social – which

interrelate with one another during a health care process (Shepherd et al. 2006). This provides

a major challenge to the use of knowledge in decision support systems; and for knowledge

management in general. Currently, knowledge management systems do not have the

capability to dynamically map tacit knowledge to the corresponding explicit knowledge

required for problem solving (Shepherd et al. 2006). Quite apart from the lack of a coherent

approach to knowledge management, some health reforms have actually adopted techniques

which have been found to be destructive to knowledge management (Southon & Cook 2001).

1. 5.3 Electronic health recordsDespite the widespread work on EHR, no widespread uptake of EHR standards has taken

place. To date, most successful information EHR systems have been implemented as

proprietary systems, or as unique systems developed by academic medical centres (Greenes

2001). Limited successes of this nature have made it difficult to use the knowledge gained from

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any of these EHR innovations for more widespread adoptions (Greenes 2001).

1. 5.4 Decision support, alerts and remindersThe Australian experience identified by The National Institute of Clinical Studies (2002) was

that, although substantial development in EDSS had taken place in Australia, much of the

development was fragmented and uncoordinated because of problems of accessibility,

scalability, duplication and lack of integration with existing systems.

The main issue for decision support systems is that their actual level of is limited by the

available medical data (Kuilboer et al. 1997) – in particular, by the paucity of structured data

(Greenes 2001). A clinical decision support system is only as effective as its underlying

knowledge base (Purcell 2005). Bates et al. (2003) suggest that some key issues for EDSS

are the timing of triggers, the ease of use of the system, the helpfulness of the content,

matching the workflow of users; and the need for messages to be highly directive.

The long experience with DSS has now allowed this group of systems to be viewed more

realistically. In particular, recent attention has turned to the unintended consequences of DSS.

A review of CPOEs by Campbell et al. (2006) identified a number of unintended consequences

of such systems, which are summarised in Table 1-2.

A survey of a CPOE system at a tertiary-care teaching hospital found that the CPOE system

facilitated 22 types of medication error risks (Koppel et al. 2005). A recent review by Coiera,

Westbrook and Wyatt (2006) which summarised the safety and quality of DSS concluded that

the usability and performance of DSS was the result of a complex set of cognitive and socio-

technical interactions – and that a deeper understanding of all these issues would result in

intrinsically ‘safer’ systems and better outcomes for the clinicians who use the systems.

The perceived poor specificity of alerts and reminders within DSS systems (e.g. for drug alerts)

Table 1-2: Unintended consequences of CPOE (Campbell et al. 2006)

ConsequenceMore or new work for clinicians.

Unfavourable workflow issues.

Never ending demands by the system.

Problems relating to the persistence of paper.

Untoward changes in communication patterns and practices.

Negative emotions.

The generation of new kinds of errors.

Unexpected changes in the power structure.

An overdependence on the technology.

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is an important issue which may impede the ability of such alerts to improve patient safety

(Glassman et al. 2002). A study by Weingart et al. (2003) found that physicians overrode

91.2% of drug allergy and 89.4% of high-severity drug interaction alerts – few physicians

changed their prescription in response to a drug allergy or interaction alert. In most of these

cases, alert overrides by physicians were justifiable on the basis of the physicians' personal

knowledge of the patient's situation. Further, while a standard exists for alerts and reminders

– Arden Syntax – collections of exchangeable alerts and reminders are not widely available

(Greenes 2001). This appears to suggest that the alerts and reminders currently available

within existing DSS systems are not sufficiently reliable to promote confidence on the part of

the using clinicians.

To sum up, despite the perception that DSS can improve efficiency and reduce costs, the

current supporting evidence is limited – and the cost effectiveness of these systems remains

unknown. Many studies have suggested that CDSS were inefficient, requiring more time and

effort from users than the paper-based methods they were designed to replace (Garg et al.

2005). Other concerns still outstanding include: workflow integration, compatibility with legacy

applications, system maturity, upgrade availability and the eroded capacity for users’

independent decision-making (Garg et al. 2005). Finally, Garg et al. (2005) believe that in

some cases cheaper, non-computerised alternatives may be equally or more effective in

improving health care and reducing medical errors.

1. 5.5 Mobile computingThe issues affecting the development of applications for mobile devices are similar to those

affecting the development of other computer applications – the most important issue for both

mobile and other technology applications is user acceptance. However, mobile devices also

present particular problems for developers, because of device size and portability.

Arshad, Mascolo and Mellor (2003) consider mobile devices (such as PDAs) to be extremely

resource-constrained in terms of memory, processing power, battery lifetime and screen size

– these issues have been reported as problems in studies on PDA use (Carroll & Christakis

2004). Users often find information difficult to read on PDAs because of the small form factor

and font size (Holleran et al. 2003). These problems require application developers to

consider: how PDA resources are used during runtime; what concessions must be made about

executing processes; and where to store information (i.e. on the PDA or remotely on a more

powerful device (Arshad, Mascolo & Mellor 2003). Addressing these problems of screen size

and computational power has occasionally involved novel approaches e.g. the use of PDAs for

information representation alongside mobile telephones for communication (Schwabe &

Frohberg 2006).

Page 17

An important concern for clinicians is the physical size of the PDA (i.e. how convenient it is to

carry) and the potential for data loss (Barretta, Strayera & Schubarta 2004). The latter is of

particular concern for clinicians if mobile devices are used to store confidential or sensitive

patient-related data.

Although many organisations have considered the use of wireless hand-held computers, such

devices are not yet in widespread use (Kuperman & Gibson 2003). The main obstacle to the

use of wireless networks appears to be speed – users report that transfer of data to their

devices is too slow (Holleran et al. 2003).

1. 5.6 privacy & securityThe public has general concerns about the privacy of their electronically stored information.

There has been recent vindication of these concerns in a study which showed major

deficiencies in compliance with the new Australian Privacy Legislation by Australian

companies – suggesting that concerns about privacy about personal information in health are

justified (Watt et al. 2002).

Health professionals' concerns about the security and privacy of personal (patient) information

are another major barrier to the implementation of DSS (National Electronic Decision Support

Taskforce 2002). Since EHR systems available over networks are vulnerable to attacks and

misuse, EHR systems require a range of security measures such as encryption, public key

infrastructure, firewalls; and network service management, software management, rights

management tools and system vulnerability management tools (Win & Cooper 2004).

Because of some of these concerns, the health community has a seen a move towards using

Intranets to share information – using the same technologies as the Internet but offering more

security (Swatman et al. 1996).

There is evidence that public opinion concerning information privacy may be changing,

however – a recent survey revealed that most of the British public considered the confidential

use of personal, identifiable patient information by the National Cancer Registry for public

health research and surveillance was not an invasion of privacy (Barrett et al. 2006). Whether

this finding will hold true across a range of national opinions, however, remains to be seen.

1. 5.7 The bottom line with IT in HealthIn summary, there are many problems to overcome in realising the full potential of IT within the

health domain. The degree to which IT systems actually support work practices found in

health, particularly clinical work, is a major issue which leads to poor acceptance of IT by

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clinicians (England 2001). Consequently, this lack of adoption of IT systems by health care

workers around the world means that health care retains the problems associated with paper-

based exchanges: hand-writing, lack of integrated information and limited availability and

capture of information at the point-of-care (Cooper, Alcock & Burgess 2003).

Some DSS strategies (including guideline implementations, alerts and reminders) have been

associated with reduced medication prescribing errors, improved preventive and chronic

disease care; and improved physician and patient satisfaction in controlled trials. But these

DSS cases have occurred predominantly in academic settings or inpatient environments – it is

therefore difficult to generalise these cases to community-based care, where most prescribing

occurs (Smith et al. 2006). Adding to this difficulty is the fact that computer-based clinical

decision support systems (CDSSs) vary greatly in design and function (Sim & Berlin 2003). In

fact, research has been undertaken to ascertain which clinical decisions might benefit from

automation, based on analyses of task complexity (Sintchenko & Coiera 2003). The bottom

line is that, while many CDSSs improve practitioner performance, the effects on patient

outcomes still remain understudied and, when studied, have produced inconsistent findings

(Garg et al. 2005).

The area of DSS is thus a rapidly advancing and unregulated field, with potential for harm as

well as benefit where systems are poorly designed and inadequately evaluated (National

Electronic Decision Support Taskforce 2002). This issue has prompted the question of whether

clinical software should be regulated (Coiera & Westbrook 2006).

Coiera and Westbrook (2006) suggest that clinical software is not subject to any procedure to

prove its safety and efficacy – compared to the complicated and highly controlled process

which occurs during the development of new drugs. They further add that, although stand-

alone software in routine clinical use may undergo rigorous evaluation by its developers,

commercial vendors can still produce (hospital) prescribing systems with significant gaps in

functionality – some even being devoid of decision rules designed to check for errors or to

guide prescribing! Unless a hospital has the expertise to develop and maintain its own

computational knowledge bases – 'an arcane and highly specialised skill set if there ever was

one' (Coiera & Westbrook 2006) – such an outcome is fraught with danger. It is, in fact, the

very strengths of DSS systems – the complex knowledge base and reasoning features and

their ability to influence physician decisions – which give rise to the ethical and legal concerns

about such systems (Berner 2002).

As these systems have the ability to harm patients, the clinician must be able to make informed

decisions on when to follow or to ignore the CDSS’s advice. In addition, knowledge bases must

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be properly maintained, and users of these systems should know how the systems were

developed and tested, the source of the rules in the system, the expectations of the user when

using the system and what user training is required (Davis et al. 2002). These authors note

that despite the technological sophistication of the American health care system, a

Commonwealth Fund 2001 Health Care Quality Survey revealed that medical care in the

American system fell short of the ideal. They suggested that having the best technology is not

enough; and that perhaps it is more difficult to explain why simple measures which are well-

known to be effective in preventing disease and managing chronic conditions are not

systematically employed (Davis et al. 2002).

So, although IT has a very powerful contribution to make to Health, IT must also be

implemented within a clearly understood framework of the knowledge processes which will

impact on its use (Southon 2003). Kaplan (2001) suggests that although controlled clinical

trials are the 'gold standard' for evaluation of DSS, a social science approach is also needed

to understand whether systems will be used or how they will be used – it is not simply an issue

of IT performance. Importantly, more qualitative studies will help to reveal the unintended

effects of IT in Health and to help understand the observed effects (Ammenwerth 2006).

Information technology has the potential to greatly improve patient safety and quality of care,

but considerably more work is required to evaluate the technologies used and their impact on

outcomes (Ortiz, Meyer & Burstin 2002).

Perhaps the redundancy built into the system of people and technologies is one explanation

why more errors do not occur – e.g. despite the many prescription mistakes made, only a

fraction end in medication administration mistakes (Ash, Berg & Coiera 2004). So, although

'we created external devices that exponentially increased our ability to calculate, analyse, and

learn' – we have some way to go before we can fully realise the potential of these devices in

Health (Jadad & Enkin 2007).

1.6 Medication management and pharmacistsEfforts towards addressing medication-related adverse events have seen the term medication

management (MM) come into common use. This term broadly describes a set of relationships

and decisions through which primary health care practitioners and patients work together to

produce specific drug therapy outcomes (Canadian Pharmacists Association 2004b).

'Medicines Management'1encompasses a range of activities intended to improve the way in

which medicines are used by patients and by government; and describes processes based on

patient need used to design, implement, deliver and monitor patient-focused care (Department

1. Medicines and medication will be used synonymously in this thesis.

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of Health Social Services and Public Safety 2004).

Stowasser, Allinson and O'Leary (2004) have described a medication management pathway

– shown in Figure 1-1 – which includes nine steps (cognitive and physical) described inside

the loop – and three background processes, shown on the outer part of the pathway loop.

This pathway is intended to apply to medication management independent of the health

setting, health professionals or the funding source (i.e. public or private).

Figure 1-1: The medication management pathway (Stowasser, Allinson & O'Leary 2004)

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The Joint Commission on Accreditation of Healthcare Organizations (JCAHO) has produced

standards which detail the elements of a medication review process; and the necessary

patient-related and medication-related information required to ensure the review process can

be carried out effectively (Rich 2004):

• appropriateness of the drug, dose, frequency, and route of administration

• therapeutic duplication

• real or potential allergies or sensitivities

• real or potential interactions between the ordered medication and other medications,

food, and laboratory test values

• other contraindications

• variation from organisational criteria for use; and

• other relevant medication-related issues or concerns.

The required patient information elements included:

• age and sex

• current medications

• diagnosis, comorbidities, concurrent conditions

• relevant laboratory test values

• allergies and past sensitivities

• weight and height

• pregnancy and lactation status; and

• any other information required by the organization for safe medication management.

A further term is used in Australia for the use of medication – the Quality of Medicines (QUM)

– which describes an overarching strategy for improving medication management rather than

a list of goals. It includes such aspects as ensuring the right patient receives the right drug in

the right dosage with the appropriate monitoring etc. According to the Australian Department

of Health and Ageing, QUM is: ‘selecting management options wisely; choosing suitable

medicines if a medicine is considered necessary; and using medicines safely and effectively’.

In a broader sense, this can apply equally to individuals and decisions that affect population

health (http://www.health.gov.au/internet/wcms/publishing.nsf/Content/nmp-quality.htm,

viewed 2006-07-11). QUM is a term used commonly used in the Australian health setting (by

pharmacists).

Pharmacists are considered to be drug therapy experts and, because of their knowledge, skills

and accessibility, pharmacists are well-placed to ensure that patients, other health care

professionals (and the health care system) can safely accomplish optimal drug therapy

outcomes (Canadian Pharmacists Association 2004b).

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The value of medication-related interventions by clinical pharmacists in the hospital setting is

well established and has been shown to be beneficial to patient management, affecting length

of stay, re-admission probability, medical procedures or laboratory monitoring – and leading to

significant savings (Dooley et al. 2003). Some further examples of effective pharmacist

interventions include:

• pharmacist-monitored anticoagulation programmes which have been associated with

reduced thromboembolic events in patients (Poon et al. 2007)

• a medical centre-based pharmacy care program which has led to increases in patients’

medication adherence leading to clinically meaningful reductions in blood pressure (BP)

– a discontinuation of the program was associated with decreased medication

adherence and persistence in patients’ high blood pressure (Lee, Grace & Taylor 2006)

• a pharmacist-based telephone patient counselling service which has been shown to

improve patient adherence and reduced mortality for patients receiving polypharmacy1

(Wu et al. 2006).

It is clear that hospital pharmacists remain important to patient health, even in the presence of

CPOE systems – the CPOE system may effectively intercept inpatient prescribing errors, but

cannot intercept medication administration errors (i.e. the errors which are possible outside the

influence of the CPOE can do that pose the highest risk of patient injury) (Wang et al. 2007).

This supports the view that maximising medication safety requires pharmacist involvement in

addition to a CPOE system (Bobb et al. 2004).

The term 'clinical' when applied to pharmacists is usually used in the context of hospital

pharmacists, although there is an evolving clinical role for community pharmacists similar to

that of the clinical pharmacist in the acute care setting (Gowan & Roller 2004). A 'general

practice pharmacist' role has also been described, in which a pharmacist is employed on-site

in a general medical practice with the aim of helping to rationalise prescribing, provide

consumer counselling on medication-related issues, run consumer-focused2 clinics, offer

prescription review and monitor drug therapy (Whitehead, Sunderland & Benrimoj 2003).

This consumer-focused model for pharmacists implies that medication reviews involve a

broader perspective of the consumer him/herself, in addition to an understanding of the

consumer's medication (Gowan & Roller 2004). These authors suggest this model should also

1. Polypharmacy refers to multiple medication use by a patient, but is mainly used in the context of unnec-essary medications

2. Consumer-focused, patient-focused and patient-centred are terms that can be differentiated on the basis of patient involvement, although there is an overlap in the way these terms are used in the litera-ture. Thus the use of these terms in this thesis will be as employed in the supporting literature, but can be considered synonymous

Page 23

include every aspect of a pharmacist's interaction with that consumer, from hospital discharge

to regular refills of prescriptions and non-prescription product requests in the community.

Consequently, within the (community) primary care setting, pharmacists provide direct patient

care; face-to-face counselling and education for their patients; prescribing advice for other

providers; advice on cost-effective drug therapy and options for treatments; and chronic

disease therapy management. In the combination of these roles, pharmacists are considered

to be essential to optimal primary health care (Canadian Pharmacists Association 2004b).

This evolving role may also lead to the development of different practice levels as hospital,

community and consultant medication management pharmacists merge more closely with

general practice and primary care initiatives (Gowan & Roller 2004). Further activities for

community pharmacists could also include: contributing to developing care programmes and

services for 'at risk' consumer groups; developing protocols for consumer counselling and self-

medication; health promotion; multidisciplinary research; and audit and drug utilisation review

(Department of Health Social Services and Public Safety 2004). Demand for this pharmacist

role is likely to be further increased because of aging populations, reductions in the availability

of GPs, shortfalls in residential care beds for patients and reductions of the informal carer

network in communities (Gowan & Roller 2004).

An important aspect of patient-focused pharmacists is that they work closely with general

practitioners and other health care professionals as a team to provide optimal patient care.

Such collaborative service delivery models involving community doctors and pharmacists have

been shown to be successful in helping resolve medication-related problems of patients

(Gilbert et al. 2002).

There is also an increasing realisation in the health domain of the importance of consumer and

health professional partnerships (National Health Information Management Advisory Council

2001; Commonwealth of Australia 2002). Consumer-centred doctor consultation has been

shown to increase consumer satisfaction, lower patient symptom burden and spare health

service resources (Little et al. 2001). Other literature concerned with physician-patient

relationships confirms the importance of participatory and patient-centred relationships in

improving patient satisfaction, medication adherence and disease and illness outcomes

(Worley-Louis, Schommer & Finnegan 2003). In the same way that good patient-physician

relationships are important for good patient outcomes, these relationships are also likely to be

important for effective patient-pharmacist interactions. However, although the patient-centred

model is widely advocated for doctors, its use in medical practice is probably rather limited –

an important reason for this the pressure on consultation time (Little et al. 2001). Such time

limitations are less likely for pharmacists who have an explicit focus on reviewing a patient’s

Page 24

medication.

MM studies have found that pharmacist interventions for community patients improve the

medication use and clinical outcomes for those patients (Frey 2003). A systematic review of

published studies (1990 to 2003) on the effectiveness of pharmaceutical care services

undertaken by Roughead, Semple and Vitry (2005) concluded that pharmaceutical care

services in the community and outpatient settings were effective. Pharmaceutical care

services demonstrated improved medication use, improved signs and symptoms in people

with asthma and improved surrogate endpoints (blood pressure, cholesterol levels,

glycosylated haemoglobin levels and medication use) – although the services reported did not

provide evidence of improved health-related quality of life for patients. Roughead, Semple and

Vitry (2005) suggested that consideration should be given to the use of adverse drug events

and resolution of medication-related problems as an outcome measure in future studies.

Gowan and Roller (2004) have suggested that in the patient-focused care role described for

pharmacists, an integration of particular knowledge and skills is required – these have been

described in and adapted within Figure 1-2. These additional information and knowledge

requirements for the pharmacist – disease states, evidence-based medicine, non-drug

therapy, interpretation of laboratory results, identification of consumer needs, consumer

monitoring skills and history-taking skills – suggests that the information and knowledge

requirements (and perhaps also the decision support requirements) of the pharmacist may be

similar to those of doctors. The ability of pharmacists to access information appropriate to their

needs has been shown to improve their ability to review the appropriateness of prescribed

drugs and identify drug-related problems (Millonig, Jackson & Ellis 2002).

However, the lack of relevant information is a major cause of medication-related sentinel

events and errors, leading the Joint Commission on Accreditation of Healthcare Organizations

to specify that ready accessibility to patient-specific information should be a principal aim for

those health professionals involved in medication management (Rich 2004).

As poor or missing information affects medical decision-making, the question of whether

missing information presents the same problem for pharmacists involved in medication

management naturally arises. Since pharmacists use the same information components as

doctors, this may very well prove to be the case.

Although IT and DSS have not had widespread success in supporting medical decision-

makers, there still appears to be a significant potential for these systems to be of benefit. This,

in turn, suggests a role for a DSS to support pharmacists involved in medication management.

Page 25

In the researcher's domain experience (and that of other domain colleagues), there did not

appear to be any existing DSS to support pharmacists, other than the traditional prescribing

and drug information systems which were part of conventional pharmacy practice – creating

an obvious lacuna which needed to be addressed.

1.7 The research problemThis chapter has introduced the health domain – an environment of rapid change, significant

cost increases and shrinking resources. The inherent complexity and problems of the health

domain challenge the ability of health professionals and the health system to deliver quality

health care safely and efficiently.

A focus of the discussion in this chapter has been medication, a treatment modality

increasingly used in the treatment of chronic disease, which now forms the basis for has been

major concerns because of the increasing prevalence of medication-related adverse effects.

Medication management was introduced as a patient-focused process which aims to improve

the way in which medicines are used by patients – to improve patient outcomes – and,

particularly, to improve the safety of medication use. The important and evolving consumer-

focused role of the pharmacist in medication management suggested that the information and

knowledge needs of pharmacists might well be similar to those of doctors involved in patient

care.

Figure 1-2: Patient care skills for pharmacists adapted from Gowan & Roller (2004)

Knowledge of disease statesKnowledge of disease states

Knowledge of evidence-based medicines

Knowledge of evidence-based medicines

Knowledge of non-drug therapyKnowledge of non-drug therapy

Knowledge of self-help servicesKnowledge of self-help services

Knowledge of laboratory monitoring

Knowledge of laboratory monitoring

Ability to provide education Ability to provide education

Ability to identify needsAbility to identify needs

History-taking &interviewing skills History-taking &

interviewing skills

Patient monitoring skills Patient monitoring skills

Communication skillsCommunication skills

Drug information skillsDrug information skills

Medication management

care plans

Medication management

care plans

Patient Care

Page 26

The promise of technology in the broader context has been questioned, because of the

complexity and nature of health-related information and communication – and perhaps partly

because of information technology failures. However, as IT (and clinical decision support

systems in particular) still hold promise in supporting medical decision-making, the question of

whether any existing and relevant technology support for medication management exists

naturally arises, particularly for pharmacists working in the increasingly important area of

medication reviews. The researcher's domain experience (and that of other domain

practitioners) suggested this may not be the case – which formed the basic focus of this

investigation. Consideration of all these issues led to the postulation of the main research

question:

Can we advance medication management for health consumers by supporting decision-making with a patient-focused information model and technology-based intervention?

Clearly, such a question is too complex to be answered as it stands. The sub-questions

emerging from this principal question are discussed in the remaining chapters of this thesis.

1.8 Scope of the researchMedication management is a concept which includes the patient and all health professionals

involved in medication-related treatment of the patient, including hospital and community

settings. However, including all possible health professionals and the patient was too complex

an investigation for a research project of this nature and time-frame. The scope of the research

was thus limited to the two major health professional groups involved in medication

management – the pharmacist and the doctor. As the pharmacist arguably takes the principal

role in medication management, the research project aimed primarily to provide support the

pharmacist's function. By improving the process for the pharmacist, the researcher believed

that the outcomes for the other partners in the medication management process would also

improve. The term 'patient-focused' in this thesis therefore describes a focus on the patient,

rather than direct patient involvement.

1.9 Significance and contributions of the researchThis thesis describes an exploration of an important and topical area of interest – the ability of

information technology to contribute to improved outcomes in health care and, in particular, the

ability of information technology to improve medication-related outcomes for patients. The

research is significant not only because it is carried out in this important area, but also because

it uses a novel empirical approach to do so.

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It is expected that this thesis will make a contribution to both theory and practice.

In theoretical terms, the research project:

• adds to knowledge and contributes to the literature of an emerging area of interest – the

application of technology to health care and, in particular, decision support tools

• will identify issues which affect the approach to development, implementation and

success of decision support tools

• adds to the empirical evidence for the need for decision support tools by pharmacists

involved in medication management

• investigates issues which underpin the development of an information model for

medication management

• adds to the understanding of decision-making and knowledge use by pharmacists and

doctors involved in medication management

• investigates the relationship between the support offered by medication-related

information models and knowledge use by pharmacists

• examines a document-centric user-interaction approach to support the medication

management process for doctors and pharmacists – in particular, the role played by a

digital document to share and communicate medication-related information

• investigates the importance of dynamic properties to the support offered by a digital

document to medication-related decision-making

• provides a substantial analysis of design research theory, significantly extending existing

studies into this approach.

In practical terms, the research project:

• aims to provide a framework upon which pharmacists and doctors can improve the

practice of medication management – in particular, safety, quality and efficiency of the

process – enabling better outcomes for patients

• identifies technology-related issues which may impact on the ability of researchers or

developers of decision support tools to undertake a technology-based intervention in the

community

• contributes to knowledge within and beyond the project by publishing research findings

• develops technology artefacts that can be used in future research to support and

improve the medication management process.

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1.10 Outline of the thesisThis thesis is structured into eight chapters which describe the background, methodology,

empirical research and conclusions related to this exploration of technology use in Health.

• Chapter 2 describes two literature reviews. The first review looked for evidence of

existing decision support tools for pharmacists in the area of medication management;

and provided the justification for this project. The second literature review investigated

and justified the technology approach – the digital document – used for this project

• Chapter 3 introduces methodological concepts and describes the selection of the

research approach based on comparisons of candidate research methods

• Chapter 4 elaborates on the chosen research method (Design Research) and discusses

its suitability for complex and dynamic environments – the health care domain – justifying

the novel use of this method in this project

• Chapter 5 is the first of three empirical research chapters, and provides a description of

an investigation of the information-rich hospital environment. Within this environment

there was an exploration of the use of information and knowledge of hospital

pharmacists and doctors involved in medication management. The results from this

scenario formed the basis for the development of the information model and XForms-

based digital document prototype

• Chapter 6 describes the testing of the hospital-centric digital document prototype by

pharmacists accredited to undertake medication reviews on patients in the community

setting. This testing refined and prepared the digital document (and consequently the

underlying information model) for the community context

• Chapter 7 describes the field studies that evaluated the digital prototype intervention –

looking for improvement in the safety, quality and efficiency of the medication

management process. The participants in the field studies were accredited pharmacists

and community doctors who were involved in medication reviews

• Chapter 8 summarises the findings from this research, draws conclusions and suggests

future research directions.

The empirical research resulted in the collection of a large amount of rich data, too substantial

to report in detail in this thesis. Consequently, the detailed analyses of data are contained in

appendices, with summaries of the analyses being included in the thesis chapters. Appendices

were also used to report source code, extensive documentation (such as approvals from

Ethics Committees) and the bibliography. All appendices, formatted as PDF files, are

contained in the CD-ROM which accompanies this thesis. The relationship of chapters and

appendices is shown in Figure 1-3. It should be noted that some appendices (e.g.

development records contained on spreadsheets) may require magnification for comfortable

viewing.

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Figure 1-3: Relationship of chapters and appendices

Chapter 1: IntroductionChapter 1: Introduction

Chapter 2: Literature reviewsChapter 2: Literature reviews

Chapter 3: MethodologyChapter 3: Methodology

Chapter 4: Design researchChapter 4: Design research

Chapter 5: Hospital scenarioChapter 5: Hospital scenario

Chapter 6: Benchtop testingChapter 6: Benchtop testing

Chapter 7: Field studiesChapter 7: Field studies

Chapter 8: Discussion & conclusionsChapter 8: Discussion & conclusions

Chapters

A: Analysis of pharmacy decision support literature

B: An Investigation of Methodology

E: Hospital Ethics Approval & relevant correspondence

H: Pharmacist Questionnaire

I: Medical Officer Questionnaire

J: Hospital – Full Analysis

K: Hospital – Technical & Development

L: Hospital – VB Viewer Code

M: Hospital – XForms Code

N: Hospital – Patient XML File

O: Benchtop – Full Analysis

R: Benchtop – VB Viewer Code

F: Benchtop Testing Ethics Approval

G: Field Studies Ethics Approval

P: Benchtop – Technical & Development

Q: Development Record (Excel spreadsheet)

T: Benchtop – XForms Code

S: Benchtop – ASP Code

U: Benchtop – Patient XML File

X: Field studies – Full Analysis

Z: Field studies – Technical & Development

AA: Field studies – XForms Code

Y: Field studies – Additional Information &Consent Forms

AD: Bibliography

V: Benchtop – XSL Code

W: Benchtop – Comparison of Model Elements (Excel)

D: HOT Fit Model Items

C: HMR Quality Assurance form

AB: Field studies – Patient XML File

AC: Field studies – XSL Code

Appendices (contained on CD-ROM)

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Chapter 2

Addressing the problem of medication-relateddecision support for pharmacists: investigating the

literature

2.1 IntroductionChapter 1 set the scenario for this research, by discussing the health domain in relation to the

complexity and problems inherent in the modern day challenges of improving quality, efficiency

and safety in an environment of rapid change, significant cost increases and shrinking

resources.

A particular focus of this discussion was the area of medication, a treatment modality

increasingly used in modern medicine. The promise of technology in the broader context has

been questioned, because of the complexity and nature of health-related information and

communication – and also, perhaps, partly because there have been some widely-publicised

technology failures.

The question for this chapter now relates to whether there is any existing and relevant

technology support for medication management, particularly for pharmacists working in the

increasingly important area of medication reviews. Informal responses from domain

practitioners suggested there was little such technology, other than traditional use of

technology for dispensing and provision of electronic drug information. This, in turn, led to a

further potential question – if no such support was currently extant, what might be a suitable

technology for this purpose?

In summary, the questions addressed by the review of the literature are, firstly:

What support is there for pharmacists for medication-related decision-making?

and, subsequently, if none existed:

What technology might provide this support?

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This chapter is structured as follows:

• Section 2.2 describes the major literature review undertaken to answer the first

question; and evaluates and summarises the findings

• Section 2.3 describes the minor literature review which provided an answer to the

second question and supported the technology approach of this project

• the chapter summary that brings together the literature findings and identifies the full set

of research questions is found within Section 2.4.

2.2 Identifying appropriate medication management support for pharmacists

2. 2.1 BackgroundAs described in Chapter 1, 2002 saw the establishment of the National Electronic Decision

Support Taskforce (NEDST) to consider the benefits and difficulties of adopting a national

approach to electronic decision support in Australia (The National Institute of Clinical Studies

2002). This taskforce undertook a fairly substantial review of the literature as a preliminary to

identifying possible solutions (National Electronic Decision Support Taskforce 2002), but found

only two pharmacy-related Electronic Decision Support Systems (EDSS), both relatively

simple systems.

Given the significant amount of activity and research in EDSS more broadly, it was

disappointing to see how little evidence there was concerning the use of EDSS in the

pharmacy sector – particularly in light of the evolving role of the pharmacist in medication

management. The major literature review, which follows in this chapter, was born from the

need to investigate any published evidence of research and/or implementation of EDSS to

support pharmacists since the NEDST report. The findings of this literature review formed the

basis for the present research project.

2. 2.2 Finding evidence in the literatureThe aim of the literature review was to identify EDSS which directly supported pharmacists or

pharmacy practice in either a hospital or community setting. This had the potential to: produce

an inventory of systems in use or under development; ascertain what type of research was

(not) being done; identify any observable deficits or gaps for EDS in pharmacy; and identify

opportunities for EDSS in pharmacy. The NEDST report provided a solid starting point but that

review was limited to randomised controlled trials. Because of the paucity of randomised

controlled trials in this area, a wider net was cast to find any implemented system for which

there was an evaluation or evidence of use. In addition, the 'clinicians' mentioned by NEDST

included physicians, nurses and allied health practitioners, while the present project focused

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on activities directly related to pharmacists and/or pharmacy practice. The NEDST criteria are

shown in Table 2-1.

A brief overview of the literature approach to the question of pharmacy decision support

follows, although a more detailed search strategy and results are shown in Appendix A.

A systematic search strategy was used to identify relevant literature. Although Pubmed was

expected to provide the vast majority of literature, additional sources were also investigated to

minimise the risk of missing any relevant literature. These included journals with known

publication of decision support articles (e.g. the Journal of the American Medical Informatics

Association) and relevant databases (e.g. Science Direct and the Cochrane Reviews

Database).

The search strategy used Medical Subject Headings (MeSH) from the US National Library of

Medicine (determined by use of the text words ‘pharmacy’, ‘pharmaceutical’, ‘decision’,

‘support’ and ’evidence’); together with combinations of selected text words ('pharmacy’,

’decision’, ‘support’, ‘evidence', 'pharmaceutical’, ‘evaluation’). The term 'decision support' has

already been discussed in the context of this research project in Chapter 1 – the project does

not attempt to develop a decision support 'system' in the traditional sense of the word, but the

Table 2-1: NEDST criteria for selection of publications of EDSS (National Electronic Decision Support Taskforce 2002)

CriteriaImplemented and in routine use by clinicians.

Used within the last 5 years (at the time of survey).

Provided clinical, rather than management, support.

Were not embedded into medical instruments.

Table 2-2: Categorisation of types of EDSS by the NEDST (National Electronic Decision Support Taskforce 2002)

Type CategorisationOne Provides categorised information that requires further processing and analysis by

users before a decision can be made.

Two Presents the clinician with trends of patients’ changing clinical status and alerts clinicians to out-of-range assessment results and intervention strategies. Clinicians are prompted to review information related to the alerts before arriving at a clinical decision.

Three Uses deductive inference engines to operate on a specific knowledge base and automatically generates diagnostic or intervention recommendations based on changing patient clinical condition, with the knowledge and inference engines stored in the knowledge base.

Four Uses more complex knowledge management and inference models such as case management reasoning, neural networks, or statistical discrimination analysis to perform outcome or prognostic predictions. Such systems possess self-learning capabilities and use fuzzy set formalism and similarity measures or confidence level computation as mechanisms to deal intelligently and accurately with uncertainty.

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literature review needed to use this term to ensure pertinent material was found.

This combined search of databases and journals identified 389 unique references. The

abstracts from these references were obtained and evaluated. Of the 389, 104 (27%) were

related to pharmacy; and 23 made reference to ‘decision support’ where this was used in a

very broad sense. One particularly interesting finding was that four papers cited in the NEDST

study were actually missed by this search. So despite what was considered a broad search, it

was still possible for some relevant information to slip through the net – highlighting a problem

when attempting ‘complete’ reviews.

Where possible, full electronic or hard copies were obtained of the 23 decision support papers;

and these were evaluated against the NEDST criteria with only four being successful. The

remaining 19 papers described professional practice or professional issues, drug safety,

pharmaco-economics, information technology, or decision making in general. The EDSS

described in these papers were also classified according to their ‘type’ described in the NEDST

report to give an indication of their level of sophistication (see Table 2-2). And even these four

papers (summarised in Table 2-3), while meeting criteria, did not describe systems of

relevance to this project, i.e. supporting pharmacists with medication management. Rather,

they described relatively simple EDSS according to the NEDST categorisation, three being

concerned with the generation of alerts and one relating to changes in pharmacist work

practices.

Amsden (2003) describes a system perhaps closest to the notion of supporting pharmacists

with medication management. This hospital-based system combined information from a

number of hospital systems and; through a rules-based system, alerts pharmacists to whether

a specific patient required review (monitoring). Although useful in itself, however, this is a good

example of a sophisticated problem-alerting system rather than relating to supporting decision-

making.

The alerting system described by Armstrong & Denemark (1998) informed pharmacists about

possible therapeutic duplication, drug interactions, high or low doses, drug overuse or

underuse; and drug-pregnancy conflicts. This on-line ‘electronic’ alert to the pharmacist was

generated by a Medicaid1 claims processor based on drug utilisation review (DUR) criteria.

This alert provided the possibility for a community pharmacist intervention (usually with the

doctor or patient) prior to dispensing further supplies of medication.

1. Medicaid is the United States’ health insurance program for individuals and families with low incomes.

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Monane et al. (1998) describe a system based on prescription claims, similar to that developed

by Armstrong & Denemark (1998), although relating to elderly patients within a Managed

Care1 system. When medications were entered into the on-line computerised DUR system

(containing previous medication claims), they could trigger an actionable alert that was sent to

the pharmacist. The alert was intended to trigger communication between the pharmacist and

doctor; and included rationales for the alert, therapeutic alternatives; and possible withdrawal

protocols – this presented an opportunity to change potentially inappropriate medication

before it was dispensed to the patient.

Murray et al. (1998) offered a particularly interesting perspective on the effect of a decision

support system on pharmacists, describing the effects of computer-based prescribing on

pharmacist work patterns following the implementation of Computer Physician Order Entry

1. Managed Care in the United States very generally describes a funded (insurance) plan that controls all aspects of the health care of the insured individuals.

Table 2-3: Pharmacy-related electronic decision support systems revealed in literature

Author(s) Title Description Outcomes Type of EDSS

Amsden, 2003 Push technology in the pharmacy. Clinical decision support helps the pharmacy department of a South Carolina medical center automate monitoring of medication effectiveness.

550 rules-based alerting system for pharmacists that combined information from the pharmacy system, laboratory system, and patient location system for patient monitoring.

38% savings in pharmacist time, 24% increase in interventions. Cost savings of US$50, 000 per annum.

2

Armstrong and Denemark, 1998

How pharmacists respond to on-line, real-time DUR alerts.

Real-time, on-line alerting system for pharmacists for prescription criteria.

20.9% of prescriptions not dispensed (medication over-utilisation, high dose, therapeutic duplication, low dose, drug–pregnancy and drug–drug interaction).

2

Monane et al., 1998

Improving prescribing patterns for the elderly through an on-line drug utilization review intervention: a system linking the physician, pharmacist, and computer.

Pharmacists alerted based on predetermined criteria for elderly patients. The pharmacist then initiated telephone-based therapeutic interventions to physicians.

Rate of change of therapeutic agent was 24% (compared to 2% expected baseline).

2

Murray et al., 1998

Effects of computer-based prescribing on pharmacist work patterns.

Work sampling of pharmacists at a hospital-based outpatient pharmacy before and after the implementation of computer-based prescribing.

Pharmacists spent 12.9% more time correcting prescription problems, 34.0% less time filling prescriptions, 45.8% more time in problem solving and 3.4% less time providing advice.

2

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(CPOE), rather than describing decision support for pharmacists per se.

Another notable observation was that three of these papers described projects in the mid-

1990’s. Recent activity in medically-based decision support activity did not appear to be

mirrored by similar current (published) activity for pharmacy.

However, a further paper relevant to the literature review was found late in the project –

‘Development of an intelligent decision support system for medication review’. This paper, by

Bindoff et al. (2007), described a knowledge-based system using a multiple classification

ripple-down rules approach, which allowed a user to identify medication-related problems

using the patient’s demographic, medical information and drug-related information. Although

the subject of this paper was highly relevant, it was based on a single test of a prototype

system using one clinical pharmacist. Thus, it still did not fulfil the inclusion criteria as it was

not an implemented system in routine clinical use.

In brief, this systematic literature review concurred with the findings of the NEDST that there

was little published evidence of pharmacy-related decision support outside systems which

traditionally support pharmacists – predominantly dispensing systems.

2. 2.3 Finding other evidenceIt is widely accepted that much information is published on-line and may not even appear in

journals or databases; and this was acknowledged by the inclusion of web sites as sources in

the NEDST review. These web sites were explored with a similar intent as for the literature

review. The web sites (viewed 2004-05-12) included: http://www.coiera.com/ailist/list.html;

http://openclinical.org/aidss.html; and http://medexpert.imc.akh-wien.ac.at/; and revealed 80

unique EDSS systems. Of these, 8 had definitely been decommissioned, but it was difficult to

ascertain whether some of the other systems were still in use. Two systems which involved or

directly supported pharmacy practice were simple alerting systems:

• DoseChecker generated pharmacist alerts for inappropriate drug dosing where it fell

outside guidelines for patients with renal impairment; and

• Microbiology/Pharmacy Expert System is a PC rules-based system producing dBase®

output and used by pharmacists to monitor aminoglycoside antibiotic dosing.

The lack of published evidence of pharmacist-specific decision support was counter to the

researcher’s personal knowledge and domain experience that such activities were occurring,

at least in Australia. And since Canada and the United Kingdom (UK) have similar health care

systems to Australia’s, there should also have been more evidence of these activities in those

locations. The researcher's familiarity with the Australian pharmacy sector prompted and

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enabled investigation of other, less obvious sources of information including Information

Technology (IT)-related papers presented at the biennial conferences of the Society of

Hospital Pharmacists of Australia (SHPA) and the Australian Quality Use of Medicines Project

Mapping website.

A review of SHPA conference proceedings (1999, 2001 and 2003) revealed that of 39 IT-

related presentations, 14 described clinical decision support (one presentation actually

reported on 4 projects). The vast majority of these were Type 1, and five systems could be

considered of Type 2. The majority of the remaining presentations dealt with use of IT for

management support, administrative or supply functions, discussions of electronic prescribing

or system implementations. About 50% of the presentations for each year concerned the use

of simple local databases for reporting activities. An interesting trend, however, was the

increase in the sophistication of topic areas over time.

The Quality Use of Medicines Project Mapping web site (http://www.qummap.health.gov.au/,

viewed 2004-05-19) provided evidence of other Australian-related activity. This site revealed

four projects of Type 1: one described the conversion of existing drug prescribing guidelines

into portable electronic format; two involved the integration of existing electronic information

products into single products; and one project aimed to provide wireless access to clinical

information for clinical pharmacists. The first three projects were not exclusively directed at

pharmacists.

Examination of the Australian scene, therefore, despite its initially promising appearance,

added little to the evidence sought for presence of pharmacy-related decision support. The

researcher’s impression of decision support activities was that they uniformly related to

information retrieval or alerting systems. The overall picture is represented in Figure 2-1.

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Without any clues from the literature about what was happening in the UK and Canada, the

path chosen for investigation of pharmacy practice perspectives was through websites of

pharmacy profession organisations in those locations. However, this proved to be a particularly

fruitless avenue.

Although there was clear evidence of IT-related activities in the UK, no status report could be

found. Of note, a conference organised by the Royal Pharmaceutical Society (’2000 and

counting – the application of IT to modern pharmacy practice’) addressed developments in the

IT area, and the introduction of new technologies into pharmacy practice (‘Forum 2000’ 2000).

The importance of IT was signified as the central conference theme, but it was interesting to

note that the developments which took precedence were primarily concerned with information

retrieval – that is, Type 1 systems. National strategies were evident in the general health

environment to support health care professionals with IT-enabled communication, patient

records and information for better patient outcomes (Department of Health 2002) and for

pharmacy IT priorities (Giles-Burness & Roberts 2002).

Personal communication suggested there was a significant amount of pharmacy decision

support activity in Canada, but this was occurring in the commercial environment and thus was

Figure 2-1: Process and results for pharmacy decision support information sources

Literature

Selected NEDST web sites

389Unique references

780Total

46Cochrane reviews

110Databases & selected journals

88PubMed text terms

536PubMed Mesh terms

References

23About ‘decision support’

104Pharmacy-related

8Decommissioned

80Unique EDSS

Australian hospital pharmacy conferences

39IT-related presentations

524Type 2 EDSS

49Type 1 EDSS

Quality Use of Medicines Project mapping site

Information sources meeting criteria

4 2 14 4

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not reported in the peer reviewed literature:

... there is certainly a lot of activity in pharmacy decision support but not a ton of reports in the peer-reviewed literature because these systems are proprietary in nature. This software area is very competitive in the pharmacy world (personal email communication, (Neil MacKinnon, May 19, 2005).

The Canadian Pharmacist’s Association’s website (http://www.pharmacists.ca/content/hcp/

Resource_Centre/Pharmacy_Practice_Research/cppr_list.cfm, viewed 2004-05-12) provided

a brief description of one information technology related project. This project, Enhancing

Pharmacist-Physician Communication Using Information Technology, was designed to

determine the feasibility of, and the proof of concept for, establishing an electronic network

between pairs of community pharmacists and family physicians to exchange information on

their patients.

Although not Canadian, the ComputerTalk website (http://www.computertalk.com/

index.html?=FromMainFrame=AboutUs.html, viewed 2004-01-19), a North American website

which publishes information about retail and community systems (Computer Talk for

Pharmacists) and hospital information systems (Computer Talk for Health-System

Pharmacies), was also assessed. Any critical evaluation was difficult as features of described

systems were at high functional levels and listed under company profiles. However, the overall

impression of the researcher was that more electronic decision support related to hospital

systems than to retail systems where there is greater emphasis on Point-of-Sale (POS)

integration, inventory, claims management, billing and (dispensing) workflow management.

Electronic information sources and decision support tended to be listed under names of other

third party providers.

2. 2.4 Was any evidence missed?Although an attempt was made to cast a wide net for recent literature, it is possible that some

references were missed. It was mentioned earlier that four of the references evaluated in the

NEDST citation list did not surface in the PubMed literature search. The focus on Australia, the

UK and Canada as areas of interest, although pertinent for comparison, may also have

imposed some limitations. This was ironically verified during the submission of this literature

review for publication in The International Journal of Pharmacy Practice (Calabretto, Warren

& Bird 2005). A European reviewer (personal communication, 31/1/2005) suggested that the

researcher had missed evidence about pharmacy-related decision support tools in Europe.

This may be true, but strengthened the message delivered in that publication that this type of

work is not published (or perhaps was not robust enough to be published?).

Although very general search terms were used, an issue could also be the use of different

keywords allocated to publications by the authors. Additionally, the restriction to the English
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language may have narrowed the results. The reporting of activities in the literature may also

be underestimated by the increasing trend to publish such information on the world-wide web;

and the fact that much information of this type may be ‘hidden’ in commercial contexts or in

conference proceedings. This adds to the general difficulty of retrieval and is exceedingly

problematic. Despite these limitations, the researcher’s domain knowledge and the use of

adapted criteria should have ensured that the magnitude of the findings was nevertheless

representative of the situation.

Despite the difficulties of identifying publications relating to decision support systems for

pharmacy, the profession is well represented in the literature in more general discussions

about decision support and, in particular, electronic prescribing and medication safety. From

the perspective of other EDS activities, pharmacy dispensing systems (both in the community

and in the hospital settings) do provide levels of electronic decision support. Most commonly,

these are alerts for drug-drug interactions, drug-allergy interactions, drug-food interactions and

drug-dose checking (e.g. maximum and minimum dose and/or frequency). Systems that are

more sophisticated may also provide alerts for drug-disease interactions, drug-laboratory

result interactions, therapeutic duplication, dose alerts in paediatrics, pregnancy or geriatrics

(although the latter are more typically provided in hospital-based systems). While it may be

possible to obtain broad system feature comparisons, there are no publications which critically

evaluate these systems, or evaluate impacts/outcomes of these features. As these systems

are commercial in nature, this is perhaps not surprising.

Therefore in answering the question:


There is little to suggest that decision support exists for pharmacists other than for information

retrieval or some cases of alert systems. While this lack does not detract from the value of

those systems, these are not suitable tools to support the process or related decision-making

in the evolving role of the pharmacist described in Chapter 1. The need to develop such tools

was thus conveyed by the (lack of) literature.

This need for ‘specialist’ support for pharmacists is no different to examples of support for

knowledge management or decision-making in the wider IT community, such as supporting

knowledge management and organisational memory in city councils (Schwabe 1999;

Schwabe & Krcmar 2000a), or integrated knowledge management to meet the challenges of

anti-terrorism initiatives for law enforcement agencies (Chen et al. 2003).

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Having identified the need to develop such tools, the next step in the research project was to

consider a suitable technology, revealed by a subsequent literature review in Section 2.3.

2.3 Looking for a technologyThe literature from this review and that supporting the introduction (Chapter 1) also provided

some guidance as to the general characteristics for a supporting technology. A sound

decision-related information and workflow model was needed to support or acknowledge:

• the increasing emphasis on continuity of care at the hospital-community interface and

coordinated care (Gowan & Roller 2004)

• the evolving and increasingly clinical role of the pharmacist in the community

(Whitehead, Sunderland & Benrimoj 2003; Department of Health Social Services and

Public Safety 2004; Gowan & Roller 2004)

• a more patient-focused approach (Little et al. 2001; Gowan & Roller 2004)

• increased knowledge and information requirements of the pharmacist (Gowan & Roller

2004) similar to medical professionals

• customisation to fit into local practice patterns, and attention to standards of care and

workflow issues to achieve acceptance by users (National Electronic Health Records

Taskforce 2000)

• the local health care contributions by pharmacists into the broader health system (Giles-

Burness & Roberts 2002).

With the confirmation of the lack of appropriate tools for pharmacists, attention turned to what

might be suitable steps to begin to address this lacuna. As the aim was to develop tools to

support contextual decision-making, an investigation of the context was required. And before

one can be informed about something, this ‘something’ must first be modelled (Berg &

Toussaint 2003). Ely et al. (2000) have suggested that a taxonomy of doctors’ questions about

patient care may enhance the understanding of doctors’ information needs and improve the

ability to meet those needs. Such a taxonomy would be equally useful in assessing the

information needs of pharmacists from the perspective of medication management (MM). The

best way to do this seemed to be to investigate pharmacists directly, as the design of

information and communication systems must include the people who will use them – since

interpretation is dependent upon the user’s specific context, culture, knowledge and resources

(Coiera 2003b). The abstraction of requirements from the ‘messiness and the concrete forms

of the work practices’ as well as being a necessary step in requirements elicitation also

facilitates user interaction in the process (Berg & Toussaint 2003).

As the MM process involves doctors and pharmacists, there was also a need to investigate the

doctors’ involvement in; and perception of the MM process. Bates and Gawande (2003) note

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that it remains difficult to change clinical practice, adding that it is important to understand the

impact of decision support when identifying the common elements of success in this area.

Therefore, in the first stages of this project it was important to identify a taxonomy that allowed

the categorisation of information needs, sound understanding of the ‘information space’

(Coiera 2003b); and the communication contexts that affected good decision making.

As no tool for this purpose was evident in the literature, there was similarly no expectation that

a taxonomy or model for the concept of medication management would exist – and none was

found. The ‘medication models’ cited most commonly describe processes or guidelines, rather

than the issues relevant to this project.

A commentary by Cameron (2005) on medication management models and other pharmacist

interventions described two models:

• The first Medication Management Model was well described in the literature, although it

actually referred to a medication review process involving a home care nurse, consultant

pharmacist and primary physician using a set of guidelines to address four high risk

medication problems in the high-risk elderly population (Frey & Rahman 2003). These

problems included: prevention of unnecessary therapeutic duplication; issues related to

cardiovascular medication; use of psychotropic drugs in patients with recent falls; or

confusion and psychotropic drugs in patients with assessment of recent confusion.

These guidelines had grown out of earlier published criteria for determining potentially

inappropriate medication use in the elderly (Beers 1997) and have been subsequently

been updated (Fick et al. 2003).

• A second model was the pharmacist intervention program, PHARMAssist which consists

of six monthly meetings between participants and pharmacists to discuss correct and

safe medication use, supported by a medication record that participants are encouraged

to maintain and share with other health care providers (Cameron 2005).

Other (medication management) models mentioned in the literature described broader

applications of the term, including collaborative service delivery (Gilbert et al. 2002), disease-

based pharmaceutical care such as asthma (Saini, Krass & Armour 2004), primary care

pharmacy (Carmichael et al. 2004) and substance use disorders in patients with severe mental

illness (Mueser, Drake & Wallach 1998). Lacking an existing model on which to base this

project, it was clear that one would have to be developed from first principles.

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However, even if a suitable taxonomy could be described, the next research question

remained:


Chapter 1 attested to the difficulty of designing ‘decision support systems’ in general and

suggested that important elements were flexible information representation and

communication. Early consideration of a supporting technology by the researcher indicated

that a document metaphor might have the appropriate expressiveness and flexibility to support

the aim of the project. The background to this view is revealed in the next sub-section.

2. 3.1 Why a document?The document remains the pervasive way of representing information regardless of the

progress and similar intent of the Internet; and paper is still an important aspect of information

representation (McNurlin & Sprague 2005, p. 280).

Further, despite various technologies available for content storage and manipulation, much

content for human use is still understood and processed in the form of documents (Honkaranta

2001). Primarily as paper forms, documents are still the most common vehicle for carrying out

processes, carrying information and accumulating input from a chain of people as they

(documents) move through organisations (McNurlin & Sprague 2005, p. 285). In a typical

organisation, 80%-90% of the recorded information is represented as documents rather than

as highly structured data for manipulation (Honkaranta 2001). In addition, as individuals may

have no, or only infrequent access to the Internet, a case could be made for maintaining both

means of representation (McNurlin & Sprague 2005, p. 282).

A document-oriented user-interaction paradigm is an intuitive way of supporting clinical

documentation, as well as an effective mechanism of allowing information communication

between individuals involved in the health care process (Lenz et al. 2002). Berg and Toussaint

(2003) state that what makes paper (documents) particularly well-suited in supporting Western

medical work is their ability to accumulate data during a patient trajectory; and coordinating

activities and events at various locations or times. The researcher’s domain experience

confirms that most health-related information is contained in a broad range of general purpose

and specifically designed documents used to share or communicate information, or as

personal repositories. The document-oriented view of a data structure (supported by XML),

also matches the organisation of health care data very well (Schweiger et al. 2005). In addition

to content and communication, documents (in a broad sense) can also have other benefits for

users, such as allowing adaptability, flexibility, portability and visibility (Fitzpatrick 2000a),

providing virtual meeting places (Toomey, Adams & Churchill 1998); and also taking on social

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roles (Brown & Duguid 1995) – benefits which are discussed later. The nature of what a

document ‘is’, forms the basis of much debate in the literature. As it is important to understand

what role a document was going to play in the framework of this project, some relevant

discussion is offered.

2. 3.2 What is a document?

2. 3.2.1 The historical perspectiveHistorically a document is associated with paper, e.g. defined by the Macquarie Dictionary as

‘a written or printed paper furnishing information or evidence’ (Delbridge 1982). Other

definitions move away from the object and instead concentrate on the content, e.g. a unit of

'recorded information structured for human consumption' (McNurlin & Sprague 2005, p. 280).

Van der Meer (1994, p. 13) in Uijlenbroek (1997, p. 17) takes this idea further and defines a

document as 'an object which has the purpose, or to which the purpose is given, to serve the

perusal of the information it contains', without mention of the technology required to examine

the document. Therefore, any data-containing item could be regarded as a document, e.g. a

letter, book, computer disk, computer chipset or even a traffic sign (Uijlenbroek 1997, p. 17).

The notion of a document has further changed over time to include reference to the fact that

IT is now a common medium for viewing documents and has progressed from simply the

notion of display, although a definitive characterisation is difficult because of the arbitrary way

in which the ‘frontier’ between documents and non-documents is discussed (Buckland 1998).

A more technology-oriented and broader definition of a document is:

... a snapshot of some set of information that can: incorporate many complex informational types, exist in multiple places across a network, depend on other documents for information, change on the fly (as subordinate documents are updated), have an intricate structure or complex data types such as full-motion video and voice annotations and be viewed and modified by many people simultaneously (if they have permission to do so) (Michalsky 1991)

Documents previously created and stored on paper are now digitally created, stored,

transferred and displayed; and the application of technology to process traditional documents

can change organisational outcomes (McNurlin & Sprague 2005, p. 280). This leads to

consideration of a ‘digital document’ in the next sub-section.

2. 3.2.2 What is a digital document?As organisational information is increasingly created and maintained as formal and informal

digital documents (Murphy 1998), the media or technology used to embody a document can

confuse the understanding of what a document actually is (Honkaranta 2001). Digital

technology consequently rekindles discussions about medium, message and meaning as

technological definitions of a document become more obscure when ‘everything is in bits’

(Buckland 1998). Buckland (1998) adds that the definition of documents needs to move away

from encompassing traditional physical forms to a definition in terms of function. For example,

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a digital document could be defined as ‘electronically recorded information flexibly structured

for human consumption’ (Murphy 2001).

There are however, some fundamental differences in how traditional and digital documents are

differentiated. Furuta (1995) lists these as:

• permanence – a digital document may never occur in a concrete, discrete form

• the reflection of importance in form – traditional documents usually contain an indication

of the their importance

• size – digital documents can vary enormously in size, ranging from words to megabytes.

Traditional documents may also be large, but unlikely to be so without requiring

computer assistance in preparation.

On the other hand, digital documents must also be differentiated from unstructured computer

files or computer databases. Again, Furuta (1995) provides guidance. A digital document is:

• a self-contained unit or intellectual contribution

• formed from component parts and relationships among those components

• intentionally authored, reflecting the author's intention with semantic relationships among

components.

These characteristics of course, equally apply to the authoring of ‘traditional’ documents.

Given the ubiquitous and blossoming nature of digital documents, no discussion of them in a

business context would be incomplete without giving some attention to the growing problem of

how to manage them – and this usually involves Electronic/Document Management Systems

(E/DMS), discussed next.

2. 3.2.3 Managing documentsDocument management and E/DMS will not be discussed in depth as while this project uses

digital documents, it is not focused on creating a ’system’ to manage digital documents. Should

the life of this digital document exceed the life of the project, however, this may need to be a

future consideration.

The consideration of documents as the knowledge assets of an organisation (in a general

sense), creates a need for mechanisms for collaboration and coordination between authors

and users; and a means to manage and evaluate increasing amounts of knowledge – this is

the intent of a well-designed E/DMS (Ginsburg 2000). Good E/DMS can also be the basis for

quality improvement and process redesign (McNurlin & Sprague 2005, p. 281). The adoption

of XML, which changes (Web) content from a human-readable, static representation (as

HTML) to a form that is ‘computer-readable’, allows more dynamic document content

(McNurlin & Sprague 2005, p. 287). Of course, this assumes that the computer has been ‘told

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what it means’ and ‘what to do with it’.

McNurlin & Sprague (2005) propose that good content management can be achieved by

understanding the goals of three phases of the content life-cycle – quality, efficiency and

effectiveness – and designing the phase with the particular goal in mind.

Tyrväinen & Päivärinta (1999) also investigate organisational E/DMS using document

classification through their document life cycle perspective (production, storage, processing

and use) and conclude that universal definitions for a ‘document’ are not suitable to conceive

organisational EDMS. They comment that this is affected by purpose of use (to observe facts,

meaning intended by the author, interpretation of data, reuse or co-ordination); and the time of

observations (when the event is recorded or the structure, knowledge or data). Within this

project, purpose of use and reuse are major considerations.

Of course, the intent of sharing document information may be from other perspectives. The

Information Continuum Model, developed by researchers at Monash University in Australia

had as its fundamental concerns, empowerment and social justice (Schauder, Stillman &

Johanson 2005).

Although general E/DMS are not relevant for this project, one particular approach to document

management based on classification did have some relevance. ‘Genres’ are used for

classification of documents for Electronic Document Management (EDM) (Karjalainen et al.

2000) or for the generation of taxonomies used in large unstructured document collections

(Müller et al. 1999). Relevance within this project was based on the potential of the genre

approach to assist with the development of taxonomies.

2. 3.2.4 GenresThe concept of genre has its roots in art and literature, where it examines how the semantic

content of text is shaped and determined by its generic nature and traditions, thus laying down

the structure, format and use of language (Toms & Campbell 1999). Genres represent one of

the many research perspectives within digital documents, which also include: hard vs. soft

documents (the latter containing inconsistencies and duplication); social interactions; support

tools; and searching (Murphy 1998).

Genre analysis involves the classification of documents based on persistent and socially

recognised combinations of form (observable physical and linguistic features) and content

(social motives, themes and topics of communication) – this is valid regardless of the media

used, and so can relate to digital or traditional documents (Honkaranta 2001; Murphy 2001).

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However, the intent is usually in relation to digital documents and newer genres can emerge

as a result of the diffusion of digital media (Tyrväinen & Päivärinta 1999). Shepherd and

Watters (1998) have described a new class of genre – the cybergenre – resulting from the

combination of the computer and the Internet. They suggest that the cybergenre can be

characterised by the triple, <content, form, functionality>, compared to genres in other media

characterised by the tuple, <content, form>. The functionality afforded by cybergenres allows

the generation of new genres, either not based on previously existing genres or substantially

different from existing genres. One application of cybergenres has been for the automatic

identification of web pages, to distinguish organisational, corporate and personal home pages

(Shepherd, Watters & Kennedy 2004).

Honkaranta (2001) has described the use of a ‘genre lens’ for requirements analysis and for

designing content workflows; and Karjalainen et al. (2000) have described a practice-oriented

method using genre-based metadata for EDM.

Instances of a genre may vary significantly not only in content, but also in ordering and other

structural elements (Murphy 2001). Yoshioka et al. (2001) use this for the formulation of

taxonomies. Genre taxonomy expresses the form of communication (purpose, content,

participants, timing, location, and form); and distinguishes between contexts of use (e.g. a

widely used report vs. a specific technical report). Progression of a genre also allows

understanding of use, change and coordination aspects thus generating ideas for improving

work processes.

As the nature of genre approach is to classify groups of documents, it became clear that this

approach was less relevant to the project. Although discussion of the different document

elements are pertinent to the project, the medication management document can be

considered a particular specialisation of a genre, as the form and communicative actions of the

document are for the specific purpose of supporting medication review.

This discussion now turns to two of the main interests for a document in this project:

information representation; and communication.

2. 3.3 The expression of information in documentsIn discussions about information, definitions of a document often focus on a single aspect and

are often metaphorical, for example ‘captured knowledge’, ’data in context’; and ’an organised

view of information’ (Buckland 1998). Otlet (1934) in Buckland (1998) defined documents as

graphic and written records representing ideas or of objects; and believed that the objects

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themselves could be regarded as documents if the user was informed by observation of those

objects. Cited examples of such documents include: natural objects, artefacts, objects bearing

traces of human activity (such as archaeological finds), explanatory models, educational

games; and works of art (Buckland 1998).

Furuta (1995) provides a useful description of a document as a meaningful, moderately-sized

unit of information, which serves as a useful abstraction in defining many types of operations.

In addition, this author believes that document components are interrelated, where

relationships are assumed to be intentionally created (by an author) (Furuta 1995). From the

perspective of a digital document, there is no suggestion that the form must be textual or

sequential (Furuta 1995), but it is the variation of content, ordering and other structural

elements (particularly the amount of structure) which provides the greatest value compared to

the invariant structures of databases (Murphy 2001).

Not surprisingly, the digital ‘document metaphor’ (certainly as expressed using XML), is

influenced by documents that individuals commonly use (e.g. faxes, product descriptions,

purchase orders, bank statements, various forms) (Erwig 2003). What makes this metaphor

usable by many is that it reflects common knowledge about the concept of a pattern and

variables that are implicit in a document (Erwig 2003). For the purposes of this project, the MM

document can become an abstraction of meaningful information with a structure reflecting

common use; and this will implicitly support knowledge used by pharmacists during medication

review.

Notwithstanding document representation being tied to intended use, it is important to prevent

structures found in traditional documents (or their computer implementations) from restricting

the interpretation of relationships within digital documents (Furuta 1995).

Murphy (2001) believes that digital documents are often ‘dichotomised’ – at one end as

passive, informal, isolated individual objects (e.g. a word processing file); and at the other as

complex, cooperative, collective, multimedia creations waiting for the right application of

advanced tools and efforts to organise them – there is little discussion about the ‘middle’ of

what is really a continuum.

This interpretive flexibility of documents therefore allows supportable adaptations of ‘messy

reality’, as they can structure practice when required; and also de-structure practice when they

don't match the expected reality (Murphy 2001). A document metaphor can therefore become

an appropriate artefact to support decision-making in ‘wicked problem’ environments such as

Health, as well as more generally in Computer Supported Cooperative Work (CSCW)

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(Fitzpatrick 1998). Fitzpatrick (1998) states that better solutions (in the CSCW environment)

can only occur through an ongoing exchange between the activities of understanding and

designing. Such knowledge-intensive work areas have also been a problem for the inflexibility

of other models such as: workflow, enterprise resource planning and software process support

(Jørgensen 2002). Therefore, ‘more powerful algorithms’ may not be the answer – new ways

need to be found to allow the human and computers parts of the ‘system’ to cooperate better

(Jørgensen 2002).

A distinct advantage of documents is that they provide visual cues – the layout of a document

contains distinctive features indicating to users the type of content likely to be contained; and

with socially familiar forms, it is even possible to identify function without labels (Toms &

Campbell 1999). The ability to use a digital document should be the same as for a traditional

document providing there is an ability to recognise these formal cues (Toms & Campbell

1999). However, the translation of these built-in clues to the digital environment does not occur

implicitly, as they may not be transferred – or even be transferable – to the digital medium,

requiring additional effort by users to make sense of the document, adding to users’ cognitive

load and potentially leading to misunderstanding and misinterpretation (Toms & Campbell

1999).

Toms & Campbell (1999) suggest that a document can be represented through a set of distinct

layers:

• document function (semantic content represented by text)

• document form (visual appearance and structure such as formatting and layout)

• document interface (how the document is accessed, used and examined).

In the paper world, these layers are represented by a variety of tactile and physical

characteristics such as the size of an item, the texture of the paper etc., and in the digital world

by a common user interface or ‘interface metaphor’. In keeping with the view earlier, these

interface metaphors need to be aligned with users’ mental models of the system, rather than

focusing too closely on system models which may lead to the risk of failure (Toms & Campbell

1999). As Jones & Dumais in Toms & Campbell (1999) note: ‘the intuitions of systems

designers are not always in accord with the needs or abilities of the user'.

It is important that digital documents carry their meaning with them as well as being able to be

read and manipulated with a variety of tools (LaMarca et al. 1999). Investigation of semantic

content in shared documents has shown that concise, unconstrained, free-text communication

is more effective in reducing cognitive overload in coordinated work around complex tasks,

compared to structured and ‘complete’ information entry or retrieval (Ash, Berg & Coiera

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2004). This is an interesting finding, particularly in light of the current desire to formulate

complete taxonomies and ontologies to support the delivery of health care. In the case of

information sharing, the flexible nature of documents, which allows weak structure for common

use and strong structure use for individual use, also allows them to act as ‘boundary objects’

between groups (Murphy 2001). This role in supporting communication and workflow is

discussed in the next sub-section.

2. 3.4 Documents in communicationAs well as being considered repositories of information, digital documents can be also be

defined as ‘adaptable artefacts, that enable communication and support workflow’

(Honkaranta 2001). This definition is often used in relation to Communities of Practice (CoP)

(Murphy 2001). It is difficult to separate workflow, coordination and communication in

discussions about shareable artefacts, but consideration here needs to turn to ‘workflow’, as

the meaning of this term used for the present project will not reflect that used in the traditional

Information Systems (IS) literature.

Traditionally, IS are designed around an idealised model of tasks (Coiera 2003b); and

Workflow Management Systems (WMS) attempt to support processes by integrating domain

and organisational knowledge (Quaglini et al. 2001). Workflow systems are also often seen as

technologies designed for organisational ordering and accountability (Fitzpatrick 1998). The

Workflow Management Coalition (WMC) defines workflow as:

The automation of a business process, in whole or part, during which documents, information or tasks are passed from one participant to another for action, according to a set of procedural rules (Workflow Management Coalition 1999)

The fundamental property of a traditional workflow process is that it is case-based (e.g. an

insurance claim, tax declaration, customer complaint); and the goal of workflow management

is to handle a large number of similar cases as efficiently and effectively as possible, based on

a process definition that specifies the order in which tasks must be executed (van der Aalst &

Kumar 2001). However, although support for routine, predictable, product-based processes is

desirable, there is the question of how much work is actually routine – probably very little

(Fitzpatrick 1998).

Commercial workflow products also assume a functional relationship between work items and

workers (i.e. each work item is executed by a single entity – either a worker or a team) where

tasks are selected and completed (van der Aalst & Kumar 2001). A problem is that individuals

within teams typically perform different roles (van der Aalst & Kumar 2001). For this reason,

business models are usually represented using data-oriented techniques (e.g. relational

models) or process models (e.g. Petri-nets) as most workflow models lack the semantics to

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concisely represent specific tasks, roles, processes, goals and organisation structures found

in business (Weigand & van den Heuvel 2002). Formal representations of workflow which exist

are idealisations that hide what is significant about ‘routine’ work, i.e. the problem-solving and

interpretation required to put procedures into action (Fitzpatrick 1998). Business models also

lack mechanisms to adequately represent the informal communication that is used to

coordinate workflows (Weigand & van den Heuvel 2002). In addition, business or health care

demands can be interrupted because of the requirements of the information flow – this can

compromise safety as well as efficiency (Mack 1998). Idealised workflow plans therefore can

become little more than a resource for situated action (Fitzpatrick 1998). LaMarca et al. (1999)

also suggest that the need to deal with content as well as coordination is a fundamental

question in the development of CSCW.

In brief, supporting workflow in a general sense is already a difficult endeavour. The health

environment poses some additional confounders that are discussed next.

2. 3.5 Workflow in HealthRestating the nature of the health domain, this is an area of knowledge intensive work typified

by non-routine work, information processing, dependence on knowledge and motivation of

workers; requiring inter- and cross-disciplinary cooperation; and networked rather than

bureaucratic organisational structures (Jørgensen 2002).

Health care organisations are different from industrial or commercial companies as their main

goals as improving the health of the public rather than achieving profit. Consequently,

outcomes are difficult to measure and processes cannot be well-defined or controlled (Quaglini

et al. 2001). The health care process is typified by many exceptions as: physicians are

independent decision-makers who may not comply with guidelines (Panzarasa et al. 2004);

and patients may be involved in decision-making about their own treatment (Mack 1998; Little

et al. 2001); and be treated by different institutions or health care professionals (Quaglini et al.

2001; Canadian Pharmacists Association 2004b; Panzarasa et al. 2004). The management of

older, chronic patients is a particularly complex process, as several disease processes are

likely to co-exist, requiring a so-called holistic approach to managing information flows

between the different individuals involved (Panzarasa et al. 2004). In addition, workflows in the

health care domain are based on intent rather than results (Klischewski & Wetzel 2003).

The domain-specific hurdles posed by this complexity must be solved before workflow systems

can become useful (Browne 2001). Beyer et al. (2004) investigated the core requirements of

health care professionals and suggested key issues were flexibility, adaptability, robustness,

integration of existing systems and standards, semantic compatibility, security and process

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orientation. These are a daunting and complex list of demands matching a complex, dynamic

socio-technical system.

Understanding workflow is particularly important when designing applications for clinicians

(Bates et al. 2003). For example, the acceptability of a prescribing DSS is dependant on its

ability to avoid interference with patient-doctor interaction or the consultation workflow (Ahearn

& Kerr 2003). Mack (1998) states that considering workflow in health care actually needs

careful attention to the ‘patient's footsteps’ (Mack 1998).

There have been attempts to create Computer Interpretable Guideline (CIG) representations

for patient-specific decision support that will not interrupt clinical workflow (Elkin et al. 2001).

An example of such a system – although not a particularly successful one – is the 'disease-

state' flow model, used in the PRODIGY Project to represent therapeutic approaches (e.g.

drug monotherapy followed by combination therapy for hypertension) (Barretto et al. 2003).

However, it is import to note that for health professionals, working on a computer is rarely an

isolated task as they are always communicating with others (Ash, Berg & Coiera 2004).

Against this complex picture of health, there is the need to support informal aspects of the work

process (Fitzpatrick 1998), to integrate workflow with aspects of information integration

(Barretto et al. 2003); and support communication (Panzarasa et al. 2004) – this proposes the

use of relatively unstructured workflows (Barretto et al. 2003). This initially suggested that

document-centred collaboration could provide a coordination infrastructure similar to a

workflow process while allowing conventional use of digital documents. Examples of such

approaches to workflow in Health are introduced in the next section.

2. 3.5.1 The flow of work in HealthGiven the flexibility required in the health care domain, it might be better to talk about the ‘flow

of work’, because the nature of the work undertaken can vary for each individual (as opposed

to repeating tasks) and also because the flow is highly dependant on intent or outcomes of the

work task. Some different approaches to workflow in health as a better reflection of needs –

service flow, document flow and ‘care flow’ – are briefly overviewed.

Klischewski & Wetzel (2003) have suggested a service flow modelling approach where: each

workplace is a service point; flowing data represent customer relations (not the products to

work on); process models are resources for personalisation; and process control is

decentralised (there is no central flow engine). In this scenario, information flow accompanies

the patient's move through the service provider network. However, these authors also note that

there are two particular aspects opposing the development of suitable infrastructures in the

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health domain. Service work might last longer than the patient's presence at a service point

(i.e. treatment issues continue after a visit to a General Practitioner or medical specialist); and

the existing IT infrastructure needs to be considered, as it can range from scenarios of ‘poorly’

IT equipped physicians to large hospitals using sophisticated IT (Klischewski & Wetzel 2003).

Bernauer, Kappel & Michlmayr (2003) suggest traceable document flows (TDF) as an

alternative, light-weight infrastructure for workflow management in environments where a

workflow management system is not available and/or impossible to deploy. This is based on a

peer-to-peer (P2P) model that allows for the collaborative editing of documents. Metadata is

used to describe document flows across a network – in this way, workflow analysis can be

carried out by investigating document flows (Bernauer, Kappel & Michlmayr 2003).

Panzarasa et al. (2004) describe the concept of a Careflow Management System (CfMS)

which handles the information and (internal and external) communication needs that underlie

chronic disease management. A CfMS involves procedures (e.g. documents, shared

information and task assignment) being passed from one participant to another according to a

process definition. Careflows are case-based, a case being the process execution for a

particular patient. When a new instance of a Careflow takes place, a generic task will be

defined as a work item for the care of an individual patient alongside the required resources

(either human or non-human). This application also provides forms for data entry, data retrieval

and visualisation. Of particular importance is that the CfMS deals with possible exceptions

arising during the instance execution and generation of worklists. The CfMS represents the

best practice knowledge suitable for the management of those patients; and optimises the use

of end-user application components, such as electronic patient records, management

systems, and interaction between agents involved in the care process (e.g. patients, nurses,

clinicians, etc.) (Panzarasa et al. 2004).

These examples illustrate attention to a range of factors which require consideration in health

and although this project does not attempt anything as ambitious as these systems, the overall

philosophy is similar.

In summary, even within discussions of 'conventional' workflow models, problems exist

because of the difficulty of exact task definitions, exception handling; and the need to consider

organisational structures and information flows. Health defies the application of conventional

workflow concepts because it is a complex and dynamic environment. In particular, the

interaction between a patient and many health professionals, the large number of exceptions,

and the constant requirement for information sharing and communication points to an

unstructured and flexible workflow process. A natural solution appears to be to fit the ‘workflow’

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to the patient, where this reflects the flow of care. Although the present project looked at a

smaller component of patient care, namely medication management, the same issues are

relevant. The notion of a document metaphor, implemented as a digital document that was

'self-aware' and supported information sharing and communication by being itself the artefact

of workflow appeared to be a promising approach.

A further important dimension of health care is that information is not simply moved on to the

next user. As the patient moves through the system, there is a requirement for collaboration,

cooperation and coordination to ensure that decision-making considers all appropriate

information and receives the attention of all appropriate health professionals. This dimension

is discussed in the next sub-section.

2. 3.6 Collaboration, Cooperation and CoordinationHealth can be considered to have communities of practice (CoP). In a general sense these are

‘groups of people informally bound together by shared expertise and passion for a joint

enterprise’, who share experiences and knowledge in novel ways, develop new approaches to

problems, promote best practice, develop professional skills, can exist within (business) units

or across divisional boundaries, are self organising and fundamentally informal (Wenger &

Snyder 2000). Not all of these features are found for all health professionals or practice

scenarios, but this does describe many aspects of professional practice well. Aspects of

collaboration, cooperation and coordination are becoming ever more important as the

provision of health care increasingly changes from isolated treatment episodes to a continuous

process involving multiple health care professionals and institutions, with the consequent need

for an ‘information system’ to support processes across the whole of health care (Beyer et al.

2004).

CoPs require tools to carry out practice and to interact with outside entities – digital documents

are possible candidates for this (Murphy 2001). Murphy (2001) sees documents as having

three roles: objects of practice (conveying practice-related information); making practice

visible; and as mechanisms to bridge between CoPs. LaMarca et al. (1999) see collaboration

as a function of a document artefact (rather than the application) and the digital document as

the central means of content exchange. Sometimes, however, electronic communication can

change the nature of boundaries and work-practices in unexpected ways and there is a

challenge to also focus on the social boundaries as artefacts are enacted (Fitzpatrick 2000b).

Fitzpatrick (2000b) cites the advantages of implementing a digital radiography system – this

enabled new forms of communication among individuals with the common goal of shared

patient care. The new forms of communication (electronic orders, digital x-rays and on-line

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reports) changed the nature of the work practice boundaries, shortened the phases of

interaction, diminished the constraints of physical boundaries; and allowed more direct

interactions between the specialists and the doctors requesting the order. These artefacts had

created transparent communication pathways to support relationships previously unsupported

by the previous pathways (Fitzpatrick 2000b).

As well as supporting information sharing and communication, documents provide other

benefits in and of themselves. Sub-section 2.3.5 mentions some of those benefits which were

of particular interest to this project.

2. 3.7 Other advantages of documents

2. 3.7.1 Self awarenessLaMarca et al. (1991) argued for the need for ’situationally aware’ documents, responsive to

changes in their use and users. They saw the ability to associate computation with content to

give the ability to bind application semantics with content, making the documents in effect

situationally aware. A desirable feature of the artefact in this project was the notion of context

– did the document know ‘where’ it was, for example with a doctor or pharmacist? TDFs

(described earlier) also used versions of documents at different locations to form the basis for

modelling the distribution aspect and allowing a modified relationship to a person (Bernauer,

Kappel & Michlmayr 2003), but such a notion was outside the scope of this project.

2. 3.7.2 Social rolesAnother important aspect of documents is their social role. Society often focuses on the

‘commercial life’ of documents, but Brown & Duguid (1995) believe we should also remember

the social uses of documents. It is this social life or social world (cyberspace) created by digital

documents that has led to the enormous success of the Internet (Brown & Duguid 1995). As

anticipated in this project, the document metaphor can enable authors, in this case the authors

of the medication management document, to connect through ‘virtual communities’ that had

been part of ‘discourses’ of the world of paper technologies (Brown & Duguid 1995). Therefore,

this project not only had the potential to improve the communication and sharing of information,

but also to assist with the social interaction of participants – a valuable ‘side-effect’.

2. 3.7.3 The paper-record as a work toolThe weaknesses of paper-based records are well documented and include illegible

handwriting, incomplete and ambiguous data, data fragmentation, poor availability; and the

danger of becoming voluminous over time, making overview problematic (Roukema et al.

2006). These factors contribute to poor continuity and quality of patient care (Roukema et al.

2006).

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However, the physical nature of the (paper) working record is embedded into the way that

patient care is practised in the social context of communication and coordination (Fitzpatrick

2000a); and the coded or written information conveyed by paper can be interpreted in different

social contexts, e.g. nursing, medicine, surgery, or the patient (Southon & Cook 2001). For

example, paper is flexible and adaptable (supporting local practice, individual preferences and

different functional views), combines functionality and communication (through location at the

point of care or specific places), embeds conversations/communications (e.g. annotations),

can make the status of work more visible (though location and access); and can be easily

moved to the point of work (Fitzpatrick 2000a). It therefore seems logical that a ‘good’ digital

document should model itself, or at least be conceived with similar notions.

Additionally, Berg & Toussaint (2003) actually suggest the reverse engineering of (some

elements of) the paper-based medical record in the development of an Electronic Patient

Record (EPR), believing that the way in which its role makes primary care processes possible

can help in understanding the models which underlie its functioning; and how they developed.

2. 3.8 Wrapping up the document discussionWith the range and breadth of definitions of documents; and the ways in which they are

implicated in information sharing and communication, it was important for the researcher to

constrain the meaning of a document to something relevant to this project – well as to some

idealised behaviour. A simple yet elegant definition previously synthesised by Uijlenbroek

(1997) was adopted as being broad enough to be inclusive of technology and simple enough

to be understandable:

A set of recorded information, regardless of its carrier, which has or had the possibilities for modification and exchange, and is manageable (Uijlenbroek 1997, p. 17-21)

The ’document’ in this project was to be an embodiment of content and presentation, context

of use, and business rules which guided its use. The purpose of the document was to inform

and to guide decision-making, acknowledging that ‘hard-to-express tacit knowledge’ was less

central than the explicit knowledge with which documents are usually identified (Murphy 2001).

The document was not to be a representation of a workflow process, decision support system

or other clinical system. The document metaphor sought an ideal representation using a digital

document which combined aspects presented in the discussion. These features are

summarised in Table 2-4.

Section 2.4 summarises this chapter’s review of the literature.

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2.4 Chapter summaryThis chapter reported and discussed the literature that was used to address two questions.

These are addressed consecutively below.


There was very little evidence of suitable technology to support the pharmacy profession other

than a few examples of relatively simple support tools, apart from the traditional practice tools

for dispensing and information retrieval. This suggested a clear need to develop an appropriate

tool to support pharmacists with decision-making or their additional information and knowledge

needs to support their expanding, patient-centred medication management roles – and provide

a means to ensure safe professional practice and optimal medication-related outcomes for

health consumers. The need for this project was consequently justified.

Table 2-4: Desirable features for the digital document

Feature CommentWill ‘look like an appropriate work document’ to the health professional using it.

Different professionals will want to view the order of information differently, for example a medical officer (MO) will likely want to observe the diagnosis or symptoms first and then be concerned about appropriate therapy – a pharmacist may be more likely to view the medication list first and then look at the rationale for use.Formatting/highlighting of information components may be different depending on how important the information is considered by the user. For example in a paediatric context, the weight may be bolded to be more apparent. Similarly, a change in value or a change to a value outside a recommended range may be highlighted.

Will contain relevant information for the decision context.

The document should be able to embody relevant information available for the medication management decision context. For example, current medication history, patient diagnosis, concurrent disease etc.

Will know about, and elicit missing information.

If there is some important information missing in the medication management context, the document should be aware of this and prompt the user to enter the information, with appropriate justification/evidence. Justification may be on the basis of clinical grounds or workflow expectations.

Will change shape as it moves to different users.

The document will be aware of where it is and therefore adapt itself to the user context. This will involve dynamic IT components to change the document for particular user contexts.

Will change shape as it accommodates individual user needs.

The document will allow flexible entry of information based on the need of the user. For example, the ability to add new medications, diagnoses or other observations.

Will be informed by relevant guidelines to support decision-making.

The document should ‘know’ about guidelines to support the requests for information, or provide anticipatory assistance. This is will not be a trivial exercise.

Will support communication between health professionals.

The document will know not only where it is, but also where it came from and where it will go, so that the user can know the information source, and if necessary go back to the source, and will know the next intended audience.

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The concept of a ‘document metaphor’, implemented as a digital document suggested itself as

a fitting approach to address this gap. This promised to support information sharing and

communication by means of a metaphor that was familiar to health professionals, as well as

providing the flexibility required for a dynamic and complex health environment. Documents by

their nature also offered other potential advantages, such as supporting some of the social

aspects of work.

The first steps towards developing such a tool were the creation of the underlying model or

taxonomy to provide a guiding foundation and a suitable technology for implementation.

Although the tool was intended for community use, the researcher decided to develop the

preliminary model through an investigation of the hospital context. The reasons for this were,

firstly, that hospital-based and community-based medication reviews have the same aim,

albeit within different contexts. Secondly, the hospital scenario would be a physically easier

environment within which to engage pharmacists and doctors – and that environment is more

‘information-rich’ for those professionals, allowing a more detailed and productive

investigation. The information model and document prototype developed for the hospital

scenario could be subjected to prototype testing to refine the model for community use. The

final model could then be evaluated in community-based medication review field studies for

impact.

These steps can be represented by means of the following research questions:

Investigation of the hospital scenario.

A. Can medication management-related issues in the hospital environment be addressed by the use of technology?

B. What technology approach might be appropriate to do this?

Model and prototype evaluation by community pharmacists

C. What are the differences in the community environment that affect the approach?

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Field studies

D. Can our intervention improve safety, quality and efficiency?

E. What is the contribution of the information model?

F. What is the contribution of the technology artefact (digital document)?

The approach taken to answer these questions is described next in Chapter 3 - Methodology.

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Chapter 3

Methodology

3.1 Introduction and Research FrameworkChapter 1 stated the main research question:


The literature reviews in the previous chapter demonstrated the need and set the ground for

this research project. As evidenced by the literature, the pharmacy profession is poorly

supported by tools to help with decision-making – expanding patient-centred roles and

additional information and knowledge needs clearly require the development of appropriate

tools, to ensure safe professional practice and optimal medication-related outcomes for health

consumers. The literature also suggested a way forward using an information model as the

basis for a digital document to support information sharing and communication.

The document model incorporating support for decision-making and workflow was developed

by the investigation of three different scenarios. The scenarios originally planned were

Australian hospital clinical pharmacy practice, home medication reviews (HMR) and the

primary care community pharmacy in Canada. However, the Canadian context was not

pursued for financial and practical considerations. Further, it was felt that it was better to

investigate the Australian HMR scenario to a greater depth to provide more richness.

Each scenario revealed further sub-goals for research that were expressed as the following

questions:




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This chapter discusses the methodology and strategy used to answer these research

questions. A more expansive discussion of research methodology can be found in Appendix

B.


• a brief introduction to relevant dimensions of research is done in Section 3.2

• an overview of IS research is given in Section 3.3

• IS methods and the selection of an appropriate method, Design Research, for this

research is discussed in Section 3.4 – a more thorough discussion of this approach and

its novel application to Health in this project is done in Chapter 4

• Section 3.5 introduces research design, however, in an attempt to avoid confusion with

the selected research method, this will be referred to as the Research Plan

• data collection techniques are discussed in Section 3.6

• the techniques used for data analysis are discussed in Section 3.7

• technology and standards applicable to digital documents are overviewed in Section 3.8

• Section 3.9 provides a project summary

• limitations of the research project are discussed in Section 3.10; and

• the chapter is summarised in Section 3.11.

3.2 Research dimensionsResearch – the ‘methodical search for knowledge’ (Friedman 2003) which contributes to the

understanding of a phenomenon (Vaishnavi & Kuechler 2005) – typically begins with real life

issues or problems (Crotty 1998, p.13). The main issues in developing a research proposal are

discussed in this section, including what methods were employed (and how they were justified,

revealing ‘assumptions about reality’) (Crotty 1998, p. 2); and how these assumptions led to

research design and data collection (Myers 2005).

Some of Neuman’s (2002, p. 20) dimensions of research – how it is done (applied or basic),

its purpose (exploratory, descriptive or explanatory) and the data collection techniques used

(quantitative or qualitative), provide a basis for describing the approach of this research. Later

sections focus on relevance and rigour; and on the contributions of the project.

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3. 2.1 How the research was doneThis project is considered applied research, as it addressed specific concerns and could offer

a solution to a problem (Neuman 2003, p. 22-23), rather than basic or ‘pure research', as the

intent was not to advance fundamental knowledge about the world, refute theory (Neuman

2003, p. 21-22), or contribute to abstract, theoretical understanding (Clarke 2000). The project

approach was also similar to variations of applied research such as instrumentalist research,

where interventions with artefacts/techniques underlie an alternative motivation to better

understand or more effectively 'design interventions' (Clarke 2000), or clinical research which

involves specific forms of professional engagement (Friedman 2003). These are areas where

a sense of research issues, background and experience are needed to distinguish among

kinds of problems and likely alternative solutions (Friedman 2003).

3. 2.2 The purpose of the projectResearch purposes or approaches adapted from Neuman (2003, p. 31) are summarised in

Table 3.1.

The nature of the research questions initially evoked an exploratory research approach, in

keeping with the objectives of becoming more familiar with a topic (Malhotra & Grover 1998),

that is, to look for ‘what’ (Neuman 2003, p. 29-30). However, the project is also descriptive

(Neuman 2003, p. 20) as an intent is the description of ‘how’ supporting the medication

management process with technology can help health professionals (‘who’) achieve better

outcomes. This suggested qualitative techniques for data gathering as they are more open to

using a range of evidence (Neuman 2003, p. 29-30); and data can be refined to identify new

possibilities and areas of interest (Malhotra & Grover 1998). Although this approach rarely

provides definitive answers, serendipity and creative questions are important as everything is

potentially significant (Neuman 2003, p. 29-30).

Explanatory research is devoted to finding causal relationships among variables (Malhotra &

Grover 1998) that is, to know ‘why’ for issues that are already known and described (Neuman

Table 3-1: Research approaches (Neuman 2003, p. 31)

Exploratory Descriptive ExplanatoryBecome familiar with basic facts, setting and concerns.

Provide a detailed, highly accurate picture.

Test a theory's predictions or principle.

Create a general mental picture of conditions.

Locate new data that contradict past data.

Elaborate and enrich a theory's explanation.

Formulate and focus questions for future research.

Create a set of categories or classify types.

Extend a theory to new issues or topics.

Generate new ideas, conjectures or hypotheses.

Clarify a sequence of steps of phases.

Support or refute an explanation or prediction.

Determine the feasibility of conducting research.

Document a causal process or mechanism.

Link issues or topics with a general principle.

Develop techniques for measuring and locating future data.

Report on the background or context of a situation.

Determine which of several explanations is best.

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2003, p. 31); and involves theory-based expectations on how and why variables should be

related on the basis of testing a relationship using a hypothesis (Malhotra & Grover 1998). This

research project does not begin with a hypothesis, nor does it aim to identify causes and

reasons – it is inductive rather than deductive.

3. 2.3 Ensuring relevance and rigourRelevance and rigour are important elements in any research, as they promise usability and

trustworthiness respectively; and are therefore worthy of some discussion here. Discussions

of relevance and rigour in the IS literature leaves an impression that relevance and rigour were

seen to be in conflict (Fällman & Grönlund 2002) This debate essentially saw academics

seeking rigour in research of interesting problems (e.g. 'unsolvable problems', such as

decision support systems); and practitioners seeking relevance in areas with lower complexity

that would have more immediate pay-offs (Westfall 1999). This section will not report that

debate, but concentrate on general aspects of relevance and rigour.

This project addressed issues or problems that practitioners actually face (Ball 2001; Fällman

& Grönlund 2002) allowing the findings to have validity-in-practice (Davison, Martinsons &

Kock 2004). In particular, the project is grounded on its application to a practical problem faced

by health practitioners, based on literature and the domain experience of the researcher. Truex

(2001) suggests that relevance might also be assured by employing research methods that

require relevance. They noted that Action Research is such a method (Truex III 2001). Design

Research, used in this research project and described later, has many aspects of Action

Research and thus relevance was further assured.

Rigour was sought through a combination of techniques described later in this chapter; and

through the researcher's own domain knowledge. In general terms, rigour can be increased by

reflecting the nature of the domain, producing data which reflect the phenomena under study;

and combining research techniques, so that the weaknesses of some are complemented by

the strengths of others (Clarke 2000), e.g. combining action research with experiments

(Mathiassen 2002).

Another major aspect of any research is its ‘contribution’. While giving general direction about

PhD research projects, Phillips and Pugh (2000, p. 63) suggest a PhD is awarded for ‘an

original contribution to knowledge’, and list ways this could be achieved. The ways that are

pertinent for this project are setting down new information for the first time, carrying out new

empirical work, applying a particular technique in a new area; and looking at areas within a

discipline not looked at before (Phillips & Pugh 2000, p. 63-64). The contributions of this project

in a general sense are discussed next in Section 3.2.4.

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3. 2.4 Contribution to knowledge and theoryThe contribution by research to knowledge is implicit in its definition as a ‘methodical search

for knowledge’ (Friedman 2003). A definition of research in the Merriam-Webster On-line

Dictionary (viewed 2005-11-13) is:

studious inquiry or examination; especially: investigation or experimentation aimed at the discovery and interpretation of facts, revision of accepted theories or laws in the light of new facts, or practical application of such new or revised theories or laws... and... the collecting of information about a particular subject

Research knowledge is not intrinsically valuable of course; and only becomes so if it is used

in, and improves practice – this is well recognised in the medical field where it is not the

research results that are important per se, but appropriate application of that information in a

clinical context (Moody 2000). Theory is also required to make an important contribution to

knowledge (Mumford 2001) – and central to the conception of theory is causality (Gregor

2002). Theory can be simple (models of elements), dynamic (describing process or action), or

describe relationships (Friedman 2003). The contribution to theory by this project was through

the development of an information model to support medication management; and through the

process of describing the support role offered by the digital document. These models could

then be used by other researchers (Neuman 2003, p. 65) to develop generalisable answers

(Friedman 2003).

Friedman (2003) also states that data and theory are interwoven; and sound theory requires

engagement with empirical reality. Theory frames research by providing concepts and basic

assumptions (Neuman 2003, p. 65); and interaction with further research findings then

becomes the basis for more theory (Gregor 2002; Neuman 2003, p. 65). The inductive

approach in this project developed theory ‘from the ground up’ as data were gathered and

analysed over time to reveal relationships (Neuman 2003, p. 65-66) (rather than being an

exercise in building, testing or extending theory) (Clarke 2000). The dissemination of results is

also a part of the outcomes of this project, ensuring that new knowledge can be applied into

practice – ensuring practical and academic relevance is particularly important in applied

disciplines (Moody 2000) – such as IS and Health.

3. 2.5 Contribution to practiceThe contribution of research to practice is also associated with the concept of relevance and

depends on the intention of the researcher and the research method (Baskerville & Myers

2004). This project had the dual intention (Davison, Martinsons & Kock 2004) of improving

practice; and contributing to theory and knowledge – within and beyond the immediate

confines of the project. In addition, participants in the project were motivated to take part by

the desire to change professional practice (Simpson et al. 2001). This research was seen very

much as a collaborative practice study (practice and research driven) with the desire to

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improve practice and add to the body of knowledge at the same time (Mathiassen 2002). Dual

intentions can also be evident in research methods. Action Research (and consequently

Design Research) seek simultaneously to create change (i.e. contribute to practice) and study

process (Baskerville & Myers 2004). Where possible, the researcher obtained pre-change

measures of appropriate variables to allow assessment of any practical improvements

(Mumford 2001) – allowing some measure of contribution by the project.

3.3 Overview of IS researchThe previous sections introduced some dimensions of research. This section now discusses

the theoretical aspects of research as a background to the approach of this project. This begins

by an introduction of the philosophical framework of research, the nature of theory and major

research paradigms and methods of analysis that influence the research approach. This

section ends with a more detailed comparison of the IS and health domains suggesting a

similar research approach in both.

3. 3.1 Philosophical frameworkResearch is described by the direction of theory and a paradigm which is the basic position

describing a set of basic assumptions shared by theories (Neuman 2003, p. 51). These two

areas are covered below. The primary focus for theory in this research is substantive (as for

specific areas of social concern) rather than formal (for broad conceptual areas) (Neuman

2003, p. 53-54). The focus also exists at the micro level as it relates to a small number of

people and small slices of time (Neuman 2003, p. 52-53).

3. 3.2 The direction of theoryTheory can be approached from two directions – beginning with abstract theory (deduction) or

observation of empirical evidence (induction). Induction is the direction of this research, first

beginning with observations of empirical evidence and then moving to more abstract

generalisations and ideas (Neuman 2003, p. 51; Crotty 1998, p. 78).

A definition of empirical is:

(an) ‘adjective based on observation or experience rather than theory or pure logic’ (Compact Oxford English Dictionary http://www.askoxford.com/concise_oed/empirical?view=uk, viewed 2006-06-07);

and empirical data:

‘originating in or based on observation or experience’ (Merriam-Webster On-line Dictionary http://www.m-w.com/dictionary/empirical, viewed 2006-06-07).

According to Gregor (2002), some of the primary purposes of the inductive approach in IS are

to build knowledge for analysing and describing (‘what is’), understanding (‘how’ and ‘why’);

and design and action (‘how to do’ something). The descriptive approach taken was in keeping

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with this dominant approach in empirical research, although it is accepted that most models

resulting from this approach will have limited explanatory power and predictive value (Clarke

2000). The deductive approach was not suitable for this project as there were no initial theories

suggesting what evidence should be gathered to support them (Malhotra & Grover 1998;

Neuman 2003, p. 51).

Having discussed some basic aspects of research, the research paradigm is considered in the

next sub-section. The research paradigm is the fundamental foundation to any research, as it

determines ‘how the researcher engages and comes to know about the world’ (Neuman 2003,

p. 90).

3. 3.3 The research paradigmMiller and Crabtree (1999, p. 8) describe the research paradigm as the patterned set of

assumptions that concern reality (ontology), knowledge of that reality (epistemology); and the

particular ways of knowing about that reality (methodology). There is no individual, correct

approach to research in social science (Neuman 2003, p. 90) and researchers must determine

what approach they will take – and then use methods consistent with that approach (Miller &

Crabtree 1999, p. 8; Neuman 2003, p. 90).

Ontology is the study of 'being', and is concerned with ‘what is’ (Crotty 1998), i.e. reality (Miller

& Crabtree 1999). Epistemology refers to the knowledge about reality (Miller & Crabtree 1999)

and incorporates assumptions of how it can be obtained (Myers 2005). Ontology and

epistemology are intertwined as the theoretical perspective that involves a certain way of

understanding what is (ontology), will also influence the way of understanding what it means

to know (epistemology) (Crotty 1998). The three main paradigms in social research are

discussed in Sub-section 3.3.4.

3. 3.4 Prevailing paradigmsThere are three ideal-type approaches to social research based on different philosophical

assumptions about the purpose of science and the nature of social reality – these approaches

seek to answer basic questions about research differently (Neuman 2003, p. 90; Myers 2005).

Although they are philosophically distinct, this is not always clear cut in the practice of

research, where there is considerable disagreement as to whether these research ‘paradigms’

(or underlying epistemologies) conflict, or can be accommodated within a single study (Myers

2005). However, they have common features as they are empirical, systematic, theoretical,

public, self-reflective and open-ended (Neuman 2003, p. 92). However, no particular paradigm

has a ‘final grasp on truth’ – the choice is most often based on the research aim and personal

preference (Miller & Crabtree 1999, p. 11). For this project, the aims and personal preferences

of the researcher suggest that the ‘truth’ is best realised through an interpretive stance. These

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three paradigms are now overviewed.

3. 3.4.1 Positivism Positivism (logical empiricism), arising from August Comte (1798-1857), seeks rigorous and

exact measure in 'objective' research where hypotheses are tested by analysing numbers from

measures (Neuman 2003) – the central concept is deduction (Straub, Gefen & Boudreau

2004).

The aim of positivism is to see the world as an:

organized method for combining deductive logic with precise empirical observations of individual behaviour in order to discover and confirm a set of probabilistic causal laws that can be used to predict general patterns of human activity (Neuman 2003)

In essence, the truth is ‘out there’, is ordered and is waiting to be discovered (Neuman 2003,

p. 72).

The ontological view assumes that this reality exists and can be measured independently of

our knowledge of it (Plummer 2001; Dubé & Paré 2003) remaining ‘value free’ (Neuman 2003,

p. 75). Parts of this reality can also be studied independently and later combined to get a

picture of the whole (Neuman 2003, p. 72).

Positivist theory generally begins from a possible causal law, logically linked to quantitative

measurements that can be subjected to statistical analysis (Neuman 2003, p. 75) and be used

for prediction (Plummer 2001; Myers 2005). Positivism also assumes that we all experience

the world in the same way (Neuman 2003, p. 77), that results can be replicated independently

(Neuman 2003, p. 73), meaning is stable and additive (Neuman 2003, p. 72); and can be

communicated to others (Neuman 1997, p. 66). Scientific theory, a cornerstone of positivism,

defines theory as one which can be falsified (Straub, Gefen & Boudreau 2004) through

hypothesis testing (Clarke 2000). Interestingly, Crotty (1998, p. 29) suggests a contradiction in

the objective or ‘scientific’ paradigm as many theories are created as heuristic and explanatory

inventions rather than being direct conclusions from data – i.e. scientists are actively

constructing scientific knowledge rather than passively observing the laws found in nature.

In keeping with the general philosophy, IS research is considered to be positivist if there is

evidence of formal propositions, quantifiable measures of variables, hypothesis testing, and

the drawing of inferences about a phenomenon from a representative sample to a stated

population (Klein & Myers 1999). The models employed are most often causal and are

validated through data (Straub, Gefen & Boudreau 2004). These factors point to a positivist

stance not being appropriate for this project, although positivist methods include field

experiments, laboratory experiments, free simulation experiments, experimental simulations,

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case studies, adaptive experiments, field studies, opinion research and archival research

(Straub, Gefen & Boudreau 2004).

3. 3.4.2 InterpretivismAs indicated by the researcher in the introduction to this section, this project was true to the

interpretive stance as it used an inductive approach, there was close engagement with

participants; and the research questions were selected and moulded based on domain

experience and intent of the researcher.

Interpretivism can be traced to the German sociologist Max Weber (1864-1920) asserting that

'facts' and 'truth' are a fantasy, that 'objective' observation is impossible and that the act of

observation-and-interpretation is dependent on the observer’s perspective (Clarke 2000).

Varieties of interpretive social science include: hermeneutics, constructionism,

ethnomethodology, and cognitive, idealist, phenomenological, subjectivist and qualitative

sociology. (Neuman 2003, p. 76). The interpretive ontological perspective is that society

constructs a social reality that is perceived differently by different individuals and meaning

comes through shared understanding – this reality can only be interpreted, not discovered

(Plummer 2001)

Neuman (2003, p. 76) describes this practically oriented approach as:

(a) systematic analysis of socially meaningful action through the direct detailed observation of people in natural settings in order to arrive at understandings and interpretations of how people create and maintain their social words.

This approach not only takes into account the researcher’s reasons and social context of

action (Neuman 2003, p. 76), but also difficulties presented by the nature of the research

domain, particularly intangible factors and relationships such as the dependence of outcomes

on the selection and definition of the research question, design of the research framework, and

definition and measurement of variables (Clarke 2000). Interpretive social science theory

essentially tells a story, representing a concept or idea, arrived at through an inductive process

(Neuman 2003, p. 77-78). Such theory is considered to be ‘true’ if it makes sense to those

being studied and if it allows others to understand the reality of those being studied (Neuman

2003, p. 79).

From an IS perspective, research is interpretive if knowledge of reality is gained through social

constructions such as language, shared meanings, documents, tools and other artefacts –

trying to understand situations through the meanings that people assign to these constructions

(Klein & Myers 1999). Orlikowski (1991) describes this as a ‘social action’ perspective on IT.

Walsham in Myers (2005) defines interpretive methods of research in IS as ‘aimed at

producing an understanding of the context of the information system; and the process whereby

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the information system influences and is influenced by the context’. Klein and Myers (1999)

suggest a set of interrelated principles to guide the interpretive approach in information

systems research:

• the hermeneutic circle

• contextualisation

• interaction between the researcher and the subject(s)

• abstraction and generalisation

• dialogical reasoning (acknowledging researcher preconceptions)

• multiple interpretations (influences of contradictions, social context, power etc. used in

revising understanding)

• suspicion.

The next approach, critical theory, is presented for completeness although it is not a stance

taken by this research. There is certainly a desire by the researcher to bring about change in

practice, but not in the social and political sense advocated by the critical approach.

3. 3.4.3 Critical theoryThis approach, which can be traced back to Karl Marx (1818-883) and Sigmund Freud (1856-

1939) is anti-positivist and anti-interpretive, using the argument that social research must be

reflective and is necessarily political (Neuman 2003, p. 81). It criticises Positivism for ignoring

social context and being anti-humanist (Neuman 2003, p. 81). In addition, it also disagrees with

Interpretivism in that Interpretivism defends the status quo (Crotty 1998, p. 113; Neuman 2003,

p. 81) and is seen to be too subjective and relativist – therefore amoral and passive (Neuman

2003, p. 81). Critical enquiry focuses on the reality of domination, distribution of power,

associated inequalities and ecological context and issues of sustainability (Miller & Crabtree

1999, p. 10). Fundamentally it adopts a realist position (that is, truth is out there) but sees

reality as constantly shaped by social, political, cultural and similar factors and evolving over

time (Neuman 2003, p. 82). Researchers taking this approach need to realise that their ability

to change circumstances is constrained by the various forms of social, cultural and political

domination (Myers 2005).

The empirical approach taken by this project must now include some discussion about data.

Although there is a clear separation is between data gathering and data analysis in quantitative

research, such a separation is problematic for many qualitative researchers (Myers 2005). This

is discussed next.

3. 3.5 Methods of analysis As the ‘analysis affects the data and the data affect the analysis’, Myers (2005) believes that

in qualitative research it is more accurate to speak of ’modes of analysis’ rather than ’data

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analysis’. These modes of analysis are the different approaches to gathering, analysing and

interpreting qualitative data. The common thread is that all qualitative modes of analysis are

concerned primarily with textual analysis (whether verbal or written) (Myers 2005). Three

approaches to data analysis are narrative metaphor, semiotics and hermeneutics; and these

are now considered.

In IS, narrative metaphor has mostly been used in understanding language, communication

and meaning among systems developers and organisational members (Myers 2005). This

approach sees people as organising their experience in the form of stories but, importantly,

there is a search for experiences which do not fit into the dominant (problem) narrative – the

potential meaningfulness to the alternative story is important (Zimmerman & Dickerson 1994).

By contrast, semiotics is primarily concerned with the meaning of signs and symbols in

language (Miller & Crabtree 1999, p. 29) where the objects function as the ‘vehicle of meaning’

but also communicate information that ‘overflows the object's use’ (Buckland 1998). The

essential idea is that words or signs can be assigned to primary conceptual categories; and

these categories represent important aspects of the theory to be tested. The importance of an

idea is revealed in the frequency with which it appears in the text. One form of semiotics

relevant to this project was content analysis – ’a technique for making replicable and valid

references from data to their contexts’ – based on patterns found in the text and used to make

inferences (Myers 2005). This approach underpinned the process of model development from

questionnaire, interview and work observation data. The implemented artefact, the digital

document, also represents a learning object as a ‘vehicle of meaning’.

The hermeneutic approach was particularly evident in this project as an underlying philosophy

and a specific mode of analysis (Myers 2005). It was true to the notion of the hermeneutic circle

regarding the connection between the understanding and interdependence of the whole and

the parts (Crotty 1998, p. 92; Klein & Myers 1999; Myers 2005). The iteration through the

different components uncovered shared meanings between the researcher and participants

(Klein & Myers 1999), developing what was already understood, and consequently clarifying

and broadening the starting point (Crotty 1998, p. 92). An affinity also existed between

participants and the researcher that helped with the emerging interpretation (Crotty 1998, p.

90). Importantly, in this research, determination of meaning was also about practical

judgement and common sense, not just abstract theorising (Crotty 1998, p. 91). Crotty (1998,

p. 91) suggests that skilled hermeneutic enquiry can gain an understanding that is deeper (in

the text) than an author's own understanding – interpreters may end up with a meaning and

assumptions that the authors themselves would have been unable to articulate.

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The discussion so far has considered research and methodological issues in the context of IS,

with the implicit assumption that these approaches would be suitable within the domain of

research – Health. The next section briefly examines the features of these two settings, and

argues that domain similarities support a similar approach for investigating a technology-

based intervention.

3. 3.6 Applicability of IS research approaches to the health environmentHealth professionals work in an increasingly complex area due to medical advances,

increasing specialisation, rising patient expectations, and the sheer size and diversity of health

service provision (Pope & Mays 1995) The interaction space within which clinicians carry out

their work is also complex as individuals communicate across rich social networks (Ash, Berg

& Coiera 2004). There are many similarities between the areas of Health and IS. Both are

multi-disciplinary fields and build on reference disciplines (Plummer 2001). Both also face

similar organisational issues when considering people and technology; and they share an

overall focus of successfully integrating people and technology to improve outcomes and

performance – they also share high failure rates of IS (Plummer 2001). Plummer (2001) also

considers health care issues to be more information intense, organisationally complex,

turbulent, paradoxical, subjective; and emotionally charged than other industries and

businesses.

The term socio-technical has equally been applied to the health system (Runciman & Moller

2001) and to IS research (Sutcliffe 2000) – the problems in both domains can also be

characterised as ‘wicked problems’ (Ritchey 2005). Much research in Health is applied

research (Pope & Mays 1995) involving human interaction; and this complexity and subjectivity

supports the need for appropriate qualitative methodologies (Plummer 2001).

As there are many parallels in IS research and HI in the nature of the organisational and

information issues (although they perhaps differ in the degree of intensity) it is reasonable to

assume that the same research methods would be useful to build theory and improve practice

in both. This topic is covered in detail in Chapter 4.

3.4 Methods in IS researchAs already mentioned, there is no single, correct approach to research and a decision must be

made about approach and consequently the methods to be used. This section gives a brief

taxonomy of research methods is IS (and appropriate in Health), overviews some research

methods that were candidates for this project; and justifies the selected method.

3. 4.1 A taxonomy of research methodsIn contrast to Computer Science (CS) which examines topics related to computer concepts at

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technical levels of analysis, IS examines topics related largely to organisational concepts

primarily at a behavioural level of analysis using evaluative research approaches (Glass,

Ramesh & Vessey 2004). IS has a number of referent disciplines (Glass, Ramesh & Vessey

2004), such as mathematics, logic, philosophy, psychology, sociology and management

(Gregor 2002), but is distinguished from these fields by the use of artefacts – and is thus at the

intersection of knowledge about properties of physical objects (machines) and knowledge

about human behaviour (Gregor 2002). One definition of IS is that it concerns ‘the effective

design, delivery, use and impact of information technology in organizations and society’

(Avison and Fitzgerald, 1995, p. xi) in Gregor (2002). Common methods in IS research are

presented in Table 3-2 (Choudrie & Dwivedi 2005).

This reliance on a range of reference disciplines (Barkhi & Sheetz 2001) can result in

significant theoretical diversity (Lee 2000; Barkhi & Sheetz 2001; Myers 2005). Also, added

confusion can arise through the use of different words for the same research methods in the

IS literature (Choudrie & Dwivedi 2005). Barkhi and Sheetz (2001) concluded that there was

not one dominant theory in use in IS research, and identified 111 separate theories from 273

articles. Despite concerns over the ‘babble effect’, a broad range of theories may in fact be

consistent with the diverse interests of the IS community, and probably not an issue as long as

the adopted theory is consistent with the situation for which it was described (Barkhi & Sheetz

2001).

Table 3-2: Common methods in IS research (Choudrie & Dwivedi 2005)

Research philosophy Minger's classification (2003) Gallier's classification (1992)

Positivist Observation (passive), measurements and analysis (statistical).

Laboratory experiments.

Experiments. Field experiments.

Survey, questionnaire or instrument. Survey.

Case study. Case study.

Theorem proof.

Forecasting.

Simulation. Simulation.

Interpretivist Interviews. Subjective/argumentative.

Ethnography. Action research.

Grounded theory. Descriptive/interpretive.

Participant observation. Futures research.

Role/game playing.

Methods involving interventions

Action research.

Critical theory.

Consultancy.

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3. 4.2 Comparison of candidate research methodsIn determining a suitable method for this thesis, the researcher considered five candidates.

The use of an artefact was central to the intervention and this intuitively suggested that Design

Research would be appropriate. Consequently, this section will not discuss the alternative

methods in detail but rather contrast their fundamental principles with Design Research to

justify selection by the researcher. A more detailed discussion of these methods can be found

in Appendix B. Design Research itself is briefly justified in this section, but is discussed in

detail in Chapter 4. The candidate methods were action research (AR), ethnography,

grounded theory, case study research and design research (DR).

3. 4.2.1 Action Research AR is applied research which treats knowledge as a form of power and abolishes the line

between research and social action; and is tied to political action where researchers try to

advance a cause or improve conditions by expanding public awareness (Neuman 1997). AR’s

strength lies in its focus on solving practical problems through intervention (Meyer 2000;

Davison, Martinsons & Kock 2004) and influencing practice positively, while simultaneously

gathering data to share more widely (Meyer 2000).

A number of principles underlie AR:

• a focus on the knowledge of action and outcomes from action (Chiasson & Dexter 2001)

• studying a phenomenon in its natural setting (Chiasson & Dexter 2001) seeking local

understandings (Stringer & Genat 2004, p. 15)

• interpreting and/or critiquing patterns of practice (Chiasson & Dexter 2001)

• playing an active role in the object of the study (Clarke 2000)

• valuing researcher and user experience in creating knowledge (Chiasson & Dexter 2001;

Davison, Martinsons & Kock 2004)

• requiring detailed data collection over a long period of time (Chiasson & Dexter 2001)

• a reflective, cyclical approach (Davison, Martinsons & Kock 2004; Stringer & Genat

2004, p.15)

• allowing findings to direct the research (Noffke 2004).

AR has been used in applied fields such as organisation development (Chiasson & Dexter

2001; Baskerville & Myers 2004), education (Baskerville & Myers 2004), system design,

training (Chiasson & Dexter 2001) and in health care settings (Meyer 2000). Scholars

researching socio-technical systems have been using forms of AR research for many years

(Baskerville & Myers 2004), e.g. for the design and study of electronic collaboration systems

(Schwabe & Krcmar 2000b).

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3. 4.2.2 EthnographyEthnography (field research or participant-observation research) (Neuman 2003, p. 363) aims

for ‘immersion’ in the lives of the people to be studied and placing the phenomena studied in

their social and cultural context (Neuman 2003, p. 363; Myers 2005). It is direct, face-to-face

social interaction with people in their natural setting (Neuman 2003, p. 364) using multiple

methods over extended periods (Miller & Crabtree 1999, p. 29). A critical part of ethnography

is ‘thick description’ – a rich detailed description of specifics rather than a summary,

standardisation, generalisation or variables (Neuman 2003, p. 367).

However, little generalisable knowledge, models or analytic methods emerge from

ethnography (Sutcliffe 2000). At the heart of ethnography is understanding beyond what is

explicitly seen or said to what is actually meant or implied in specific social contexts (Neuman

2003, p. 366). Ethnographic techniques have been applied to gather data for socio-technical

system requirements, as many problems in requirements engineering are known to have their

origins in complex social problems (Sutcliffe 2000). Ethnography has been widely used in the

study of IS in organisations, studying aspects of development and management, as a method

where multiple perspectives have been incorporated in systems design and as a general

approach in IS investigations (Myers 2005).

3. 4.2.3 Grounded theoryGrounded theory is a form of ethnographic enquiry which develops theory through a process

of systemically collecting and analysing data (Crotty 1998, p. 78; Myers 2005). More

specifically, it is inductive theory building based on empirical observations (Crotty 1998, p. 78;

Clarke 2000). The 'classic grounded theory‘ of Glaser and Strauss views induction as the key

process – ideas that are generated must be verified by the data (Douglas 2003; Heath &

Cowley 2004) – and is so called because theory is ‘grounded’ in the data from which it was

built (Power & Moynihan 2003). It shares goals with a positivist approach as it searches for

theory that is compatible with precise and rigorous evidence – and it is replicable and

generalisable (Neuman 2003, p. 52). Grounded theory is pragmatically oriented as it concerns

itself with social good and social usefulness (Seldén 2005).

As well as systematic data collection, central to Grounded Theory is data coding and writing

theoretical memos – these are used in parallel and iteratively to discover theory or revelations

in a given domain of study (Power & Moynihan 2003). Heath and Cowley (2004) note that the

aim is not to discover the theory, but a theory, to aid understanding and action. While having

its background in sociology, grounded theory has been used in tourism and hospitality

management, medical studies, psychology and, business and organisation studies (Douglas

2003), nursing and health care, and library and information science (Seldén 2005). Grounded

theory approaches are increasingly common in the IS research literature as the method is

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useful in developing context-based, process-oriented descriptions and explanations of

phenomenon (Myers 2005).

3. 4.2.4 Case study researchCase study research is the most common qualitative method used in IS (Plummer 2001; Myers

2005). The goal of case study research is to achieve exploration, description or explanation of

a particular situation, using extensive and purposeful sampling to obtain detailed information

from multiple sources (Neuman 1997; Kuzel 1999, p. 258; Clarke 2000; Yin 2003, p. 3). This

is also appropriate when researchers need to define their topics broadly or are faced with

contextual or complex multivariate conditions (Yin 2003, p. xi). This holistic approach is

particularly suited to IS research where interest has shifted to understanding complex

interactions among organisations, technologies and people (Dubé & Paré 2003); and

intangible concepts such as organisational performance and success (Plummer 2001). The

underlying principle is the in-depth examination of a few cases focusing on a few factors using

analytical logic (rather than induction) and considering the specific contexts in detail (Neuman

2003, p. 33). Often the process involves a pilot study to develop a conceptual framework and

operational measures for the ‘proper’ case study conducted later in a fresh environment (Yin

2003). While case studies can specify a causal process, generalisation is more difficult (Yin

1999; Neuman 2003, p. 33). Although this style of research is versatile as it can be positivist,

interpretive or critical (Plummer 2001; Dubé & Paré 2003; Myers 2005), it shares many

characteristics with other qualitative methodologies – the natural setting as a source of data,

the researcher as a key instrument of data collection, data collected as words and a focus on

participants' perspectives (Dubé & Paré 2003).

Case study research is considered ‘remarkably hard’ although traditionally considered to be

‘soft’ research – due to the challenges of designing a study in a systematic, manageable and

flexible manner while integrating the results into a coherent document (Dubé & Paré 2003). Yin

(1999) believes that the quality of case based studies can be improved by adopting a more

‘scientific’ approach. Case based studies are considered a suitable approach for studies in the

complex and changing domain of health, and have been used for studies in the areas of mental

health, methadone maintenance clinics, immunisation campaigns, single facility studies, policy

studies, for promising medical technologies (Yin 1999) patient illness experiences; and in

primary care in general (Kuzel 1999, p. 254). More generally, it has been used to study issues

of public policy and business administration (Yin 2003, p. xi), examine technology adoption

from organisational contexts (Choudrie & Dwivedi 2005),

3. 4.2.5 Design ResearchDesign research (science) is grounded in the ‘sciences of the artificial’ (Simon 1996), where

this is a body of knowledge about artificial (man made (sic)) objects and phenomena designed

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to meet certain desired goals (Vaishnavi & Kuechler 2005). From an IS perspective, design

science is fundamentally about addressing business needs or problem-solving (Hevner et al.

2004). The process for this is through constructing and applying innovative IT artefacts to

understand the problem addressed by the artefact and the likelihood of this approach providing

a solution (Hevner et al. 2004). As this research seeks to solve the ‘problem’ of decision-

making tools for medication management for pharmacists based on a digital artefact, this

appeared a natural fit with the design research method.

McKay and Marshall (2005) see parallels between design research and AR, in that

concomitant people, process and organisational structural changes are just as important and

relevant to improving the problem situation as the designed technical artefact. In addition (as

a socio-technical system), the essence of IS lies in the ‘contextualisation of the machine in the

social system’; and what makes design research resonate with a community that sensitivity to

social context (McKay & Marshall 2005).

The ontological and epistemological standpoints for design research suggested by Rossi and

Sein (2003) are realist (a real world exists but we are not seeking it) and that we can intervene

in the world to improve it. The research approach is qualitative and exploratory through the

development and design of systems and models (Rossi & Sein 2003).

Hevner et al. (2004) suggest that design research (in IS) addresses what are considered to be

‘wicked problems’ characterised by:

• unstable requirements and constraints based upon ill-defined environmental contexts

• complex interactions among subcomponents of the problem and its solution

• inherent flexibility to change design processes as well as design artefacts

• a critical dependence upon human cognitive abilities, i.e. creativity, to produce effective

solutions

• a critical dependence upon human social abilities (e.g., teamwork) to produce effective

solutions.

This approach is particularly usefully for new areas and where there are deficiencies in former

systems (Rossi & Sein 2003). Rigour is achieved by appropriately applying existing

methodologies, either using computational and mathematical methods, or empirical

techniques depending on the approach (Hevner et al. 2004) – and relevance is assured

through the investigation of existing problems and the contribution of new knowledge to a

community (Vaishnavi & Kuechler 2005). March and Smith (1995) in Hevner (2004) identify

two processes (build and evaluate) and four artefacts (constructs, models, methods and

instantiations) that are produced by design science (Hevner et al. 2004). The design research

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cycle consists of a number of steps: identify a need, build, evaluate, learn and theorise (Rossi

& Sein 2003). The important fundamental concepts of design research are that the process is

iterative and the philosophical perspective of the design researcher can change with progress

through the phases (Vaishnavi & Kuechler 2005). Thus, a reality created through a

constructive intervention can become the basis for new theorising and a further interventionist

cycle similar to AR methodology (Vaishnavi & Kuechler 2005).

3. 4.3 Selection and justification of the research methodThe preceding section has overviewed some candidate methods for this research project. The

intention of this research project was to investigate the application and utility of an electronic

document in the health environment for medication management. Although there is an overlap

between many of these methods from the perspectives of approach or analysis, the method

which best supported this research project was design research (DR), as central to this

research project were artefacts in the forms of the digital document and the information model

which underpinned it.

However, there were more similarities to DR than simply an artefact as a central concept. The

research was an iterative process travelling a development and refinement pathway through

hospital and community-based health scenarios. It addressed a problem of the lack of

support for informed decision-making for health professionals involved in medication

management. It was goal-oriented in attempting to understand the role of an electronic

document in supporting decision-making in health and to improve practice, in particular the

quality, safety and efficiency of the medication management process. It was contextual in that

it specifically addressed the needs of the pharmacist (and general practitioners to a different

degree) undertaking medication reviews. It involved engagement with health professionals

where the researcher was a participant-observer. In short, the project was characterised by an

ill-defined environmental context, complex interactions between problem and solution,

flexibility needed to change processes and artefact, a dependence on human cognitive abilities

to produce a solution; and a dependence on human social abilities (Hevner et al. 2004).

In addition, there were some fundamental aspects of the other methods which did not fit the

intent or nature of the project. There are obvious similarities with AR, in particular the reflective

cyclical approach to reveal a more detailed picture of the problem (and solution). However,

although the researcher had an influence on outcomes, this did not take the form of an ‘active’

participant to drive change or empower a group to change. Additionally, there was no socio-

political imperative of the sort which usually drives AR.

The main intention of ethnography is ’thick description’ – a rich description of a cultural context

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over time through immersion by the researcher. This thesis moved away from description of a

context to formulating models for practice improvement; and to a theme of iteration rather than

evolving description.

Some similarities do exist with the grounded theory approach, in particular the use of coding

to define and develop an information model. However, this was not considered a grounded

theory approach as the researcher went into the research project with prior domain experience

so the research was not ‘value-free’ (certainly not from the perspective of the original stance

of grounded theory methodology).

Case studies are common in the health environment, particularly in medicine. This research

project was not case study research as it did not seek to ‘raise questions and define

characteristics about a case’. It did rely on relatively few cases from which to empirically draw

conclusions, but, these were taken across three different scenarios, hospital, accredited

pharmacists (for benchtop testing) and in the general practitioner-pharmacist interaction

space. All data was not analysed in detail, but selected to address goals or the problems in

question. The iterative nature also differed, as with ethnography.

In summary, the strategy for this research project was empirical with an interpretivist, inductive

stance, adopting the design research method. Data collection and analysis were both

qualitative and quantitative; and data and participant triangulation were used to ensure validity.

The strategy of the research is now followed by the practical aspects of the project, the

research plan.

3.5 Research PlanAs mentioned by the researcher in the introduction to this chapter, the term 'research plan’, is

used here rather than 'research design' – so as to not confuse this with Design Research, the

research method. This section outlines the research plan, firstly in overview and then the

individual scenarios which formed the iterations through which the project proceeded.

The overall aim of this project was to improve medication management for health consumers,

through good medication management as observed by study participants. In a broader sense,

it also sought to investigate if and how digital documents could be used to support more

general requirements for a relevant health information and decision support structure. The

digital document was analysed by means of investigation of an information and work flow

model to support decision-making in the context of the evolving professional role of the

pharmacist. There was the potential to improve safety, quality and efficiency in the medication

review process with subsequent improvement in consumer outcomes.

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The information model and digital document were developed in parallel through the

investigation of three different use cases. Initially these were to be hospital clinical pharmacy

practice, home medication reviews (HMR) and the primary care community pharmacy in

Canada. The basis for the selection of these scenarios was their similar implications for

pharmacy decision support as similar requirements existed (to different degrees) in all three

scenarios. There was also a similar upstream reliance for information components (from the

medical professional writing medication orders or requests for HMR). The initial selection of

the Canadian health scenario was based on its strong parallels with the Australian scenario

and the similar patient-centred roles advocated by the Canadian Pharmacists Association. The

researcher considered that the use of a setting outside of Australia could provide additional

opportunities for providing greater richness to the model.

However, during the course of the research project it became evident that time and cost

constraints would not allow the researcher to investigate the Canadian scenario; and it was felt

that a greater focus on the community (HMR) environment would also add more depth to the

model and allow better evaluation of the artefact. The second scenario therefore became two

parts – a benchtop test of the document prototype and a field test. An advantage was that the

field test could be done with a more refined model than originally planned. In short, the use

cases became hospital clinical pharmacy practice and home medication reviews (comprising

bench top testing and field testing).

The project began with the hospital scenario (perceived to be more compact and information

dense), and this initial model was tested and refined through the other scenarios. The broad

plan was to iterate through an information collection, analysis, reflection, modelling and

prototyping loop to describe the information model and document metaphor in the context of

supporting pharmacy decision-making. Data triangulation and different approaches were used

in all scenarios to address validity.

3. 5.1 The hospital context (Part 1)Investigation of this scenario began with two questions, addressed consecutively.

A. Can medication management-related issues in the hospital environment be resolved by the use of technology?

Question A was addressed by data collection activities which for pharmacists, allowed an initial

understanding of medication-related information components, workflow and decision-process;

and for medical officers (MOs), the process for ordering medication and their perceptions to

requests for information. This allowed an understanding of important issues in medication

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management, suggested opportunities for decision support interventions, and provided a

repository of potentially helpful information flows.

This empirical, observational part of the project collected data through exploratory interviews,

observation of work practice, collection of demographic data and document analysis. Subjects

were hospital pharmacists and medical officers (MOs)1. Two to three of each group were to be

recruited from each of four major adult metropolitan hospitals in Adelaide, with the aim of

recruiting a total of at least 10 pharmacists and 10 doctors. Eligibility was based on the

participant having an appropriate role in their work scenario, i.e. a pharmacist designated as a

clinical pharmacist, and a MO who initiated medication therapy in the course of their clinical

practice. Selection was based on voluntary participation from potential subjects. There were

no specific exclusion criteria. The researcher recruited participants through Directors of

Pharmacy and Directors of Medical Administration. The former were known to the researcher

(as past colleagues). The Directors were initially approached informally by the researcher to

ascertain interest, and formal approaches for recruitment were instigated following approval

from each institutional Ethics Committee. Ethics approval was also obtained from the

University of South Australia (UniSA) Human Research Ethics Committee. The research

proposal for the hospital scenario (including data collection tools) is contained in Appendix E.


This question was addressed by the use of XForms technology. As the consideration of

technology was a major issue, this is discussed by the researcher in detail in Section 3.8.

3. 5.2 The community context: prototype bench testing (Part 2A)Part 1 provided the empirical basis for a model of information flow centred on the hospital

clinical pharmacist; and identified opportunities for improved support for that role. This next

scenario (Part 2A) addressed the next research question:


The data collection goals of this phase were to add to knowledge gained in the hospital

scenario, refine the information model for use in the community HMR scenario and develop the

digital document prototype. This used experiential information and opinion from pharmacists

carrying out HMRs; and who interacted with General Practitioners (GPs) in the community. In

addition, the process for GPs requesting HMRs needed to be understood; and goals needed

to be defined for the intervention planned in the field study.

1. Medical officer (MO) is a generic term commonly used in Australian hospitals to refer to doctors.

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Data were collected from interviews, prototype testing and a focus group. User reactions,

suggestions for improvement and innovation during testing of the digital document prototype

were used to progress the information and interface models. Participants in this scenario were

community pharmacists (a minimum of five pharmacists) undertaking HMR – prototype testing

aimed for pharmacists to enter a minimum of 25 HMR referrals (five each). Participant eligibility

was based on their being accredited to undertake HMRs; and inclusion into the project was

based on voluntary participation from potential subjects. The researcher recruited participants

through the HMR Pharmacist Facilitators of the Southern, Western and North-eastern

Divisions of General Practice in South Australia.

The research proposal for the benchtop testing scenario (also containing the data collection

tools) is shown in Appendix F.

3. 5.3 Medication review field study (Part 2B)This last part, 2B, concluded the project with a field study of the document prototype. In this

phase, the nature of research changed from exploration, understanding and development to

investigating effect, i.e. practice changes caused by the intervention. As for the previous

scenarios, initial research goals were transformed to research questions:

D. Can the intervention improve safety, quality and efficiency?



These questions were to be answered by perceptions from study participants and certain

qualitative markers shown in Table 3-3. These markers represented only a starting point as

the study sought opportunistic measures and opinions to measure the value or effect of the

intervention. Data were collected from analysis of prototype use, interviews, focus group and

document analysis. In addition, further document analysis for quality parameters was to be

undertaken by an independent review panel of three relevant domain experts consisting of at

least one doctor and one accredited pharmacist. Participants were pharmacists and general

practitioners (GPs).

A minimum of two practice groups were sought, where a group consisted of a community

medical practice undertaking medication reviews using accredited pharmacists. Participant

eligibility was based on informed, voluntary participation of individuals from identified

practices. The researcher recruited participants using direct approach to practices identified

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through the HMR pharmacist facilitators of the South Australian Divisions of General Practice,

participants from previous phases of this study or opportunistic communications with other

pharmacists. Patient consent is routinely required for patients undergoing HMRs, but the

researcher also determined whether the GPs and pharmacists had any additional consent

requirements for patients to be considered in the project.

Figure 3-1 graphically summarises the relationship of the research questions to the different

phases of research and the literature review. The research proposal for the field studies

(containing the data collection tools used) is shown in Appendix G

.

Table 3-3: Qualitative measures for the HMR field test

Can we improve? Measures/markers

Safety Reduced medication errors.Reduced adverse events.More timely consideration of HMR report.More current patient information.

Quality Improved clinical documentation.Increase time for direct patient care.Increased application of clinical guidelines/pathways.Health professional satisfaction.

Efficiency Increased speed of the MR process (report delivery, report acknowledgement).Reduced transcription.Reductions in tests.Changed patterns of drug prescribing.Improved pharmacist-GP communication.

Figure 3-1: Research questions in relation to research phases

Part 1 – The Hospital Scenario

Part 2 – The Community Scenario2A – Investigation of the

home medication review context: prototype bench testing

2B – Medication review field study

Literature review

Can we advance medication management for health consumers by supporting decision-making with a patient-

focused information model and technology-based intervention?

D. Can our intervention improve safety, quality and efficiency?E. What is the contribution of the information model?F. What is the contribution of the technology artefact (digital document)?


B. What is the best way of implementing this technology

approach?




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3.6 Data collection techniquesThe research plan introduced the data collection techniques used in the project. These are

now described in more detail to demonstrate the nature of these techniques and the thought

required to use them. However, this is preceded by some discussion on the nature of the data

collected and the use of triangulation to ensure validity of the research.

3. 6.1 Quantitative and qualitative dataThe majority of data collected within the project (comparisons, documents, transcribed

recordings, observations and interviews) was descriptive and therefore qualitative (Coffey &

Atkinson 1996, p. 4; Neuman 1997, p. 30), although some quantitative data was collected for

descriptive statistics. In addition, as one of the research questions in the field study was

concerned with identifying improvement based on the intervention, appropriate data to allow

pre- and post-measurement was also planned.

The labels 'quantitative' and 'qualitative' are often used in the literature to describe schools of

research – this use is misleading, as these terms better describe the nature of the data

gathered in empirical research (Clarke 2000). Qualitative research does not constitute a

paradigm in its own right (Coffey & Atkinson 1996, p. 12) and the distinction between

qualitative and quantitative research occurs at the level of methods, not at the level of

epistemology or theoretical perspective (Coffey & Atkinson 1996, p. 13; Crotty 1998, p. 15). In

fact, the use of qualitative and quantitative techniques is seen to be complementary (Pope &

Mays 1995)

3. 6.2 Validity through triangulationThe important issue in qualitative research of how to ensure validity (Davison, Martinsons &

Kock 2004), reliability; and how to protect against bias (Mays & Pope 1995; Shaw 2001) is

addressed through triangulation. This is achieved by the use of more than one: source of data,

investigator, theory, methodological approach, environment; or setting (Malhotra & Grover

1998; Clarke 2000; Mays & Pope 2000; Guion 2001; Shaw 2001; Davison, Martinsons & Kock

2004). However, the type of triangulation used will depend on its feasibility and

appropriateness to the research question (Guion 2001).

Mays (2000) suggests that triangulation by data as a test of validity may be open to question

– it assumes that weaknesses in one data collection method will be compensated by strengths

in another and that it is always possible to judge between different narratives (e.g. from

interviews with clinicians and patients). However, data triangulation is commonly used; and

was used by the researcher in this project as being the easiest and most feasible. Data

collection techniques are described in section 3.6.3.

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3. 6.3 Data collection techniques

3. 6.3.1 Literature reviewThe literature review – the account of what has been published on a topic by accredited

scholars and researchers (Taylor & Procter 2005) – is considered an early step in the research

process irrespective of the approach adopted (Neuman 2003, p. 96). The principal literature

review undertaken for this project described in Chapter 2, sought to identify what support there

was for decision-making for pharmacists outside of traditional roles. This was in was in keeping

with the goal to ‘integrate and summarise what in is known in an area’ (Neuman 2003, p. 96);

and to provide the background and justification for the research questions (Bruce 1994).

Further literature was reviewed to gain familiarity with other bodies of knowledge – in

particular, to seek a possible technology solution – supported by literature on digital

documents and workflow, also discussed in Chapter 2. The researcher also sought

supplementary literature in the areas of research methodology, health (particularly relating to

medication safety, pharmacy practice and e-Health), standards (relating to the health-IT

environment) and technology such as XForms.

3. 6.3.2 Use of questionnairesThis project used semi-structured questionnaires as a primary exploration of medication

management issues. The mixture of closed and open-ended questions allowed some

quantification of responses as well as exploration of issues and attitudes (Kendall & Kendall

1988, p. 156; McColl et al. 2001, p. 45). Piloting a questionnaire on participants who are

representative of the target sample is seen to be a success factor for a good questionnaire

(Boynton 2004) – this was less of an issue for this project as the questionnaire was intended

as a preliminary step where (largely) open-ended questions allowed the participant time to

consider questions passively (Maciaszek 2001, p. 83). The follow-up interview (using a filled-

in questionnaire as the interview tool) solved any issues about clarifying questions (Maciaszek

2001, p. 83). Similarly, other factors such as the order of questions, format and choice of words

that can be important in self-administered questionnaires (to avoid issues such as bias)

(Kendall & Kendall 1988, p. 162-176) were not an issue because of the approach used.

However, the researcher acknowledges that because of the range of considerations that affect

questionnaire design (about which decisions have to be made) questionnaire research can

never be objective (Miller & Crabtree 1999).

3. 6.3.3 Use of interviewsIn keeping with an exploratory aim of the research, the interviews were face-to-face and in-

depth, building on the information collected through the initial questionnaire. The importance

of in-depth interviews using (the same) open-ended questions was to illicit rich, detailed

material (Mahoney 1997); and importantly for the researcher to capture opinion and not simply

uncover facts (Kendall & Kendall 1988, p. 125). The need for well-qualified interviewers was

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addressed by the fact that the researcher had significant domain experience – interviews with

domain experts are often a simple knowledge transfer process (Maciaszek 2001, p. 82). The

researcher’s domain knowledge also avoided problems of vocabulary, allowed participants to

be at ease and provided avenues of questioning in addition to those planned in the

questionnaire (Kendall & Kendall 1988, p. 130). Interviews were audio-taped as well as being

subject to further note-taking, as this was important to provide a complete record and an aid to

recall (Kendall & Kendall 1988, p. 140).

3. 6.3.4 Work practice observationObservations provided an opportunity for the researcher to collect data on behaviours,

interactions, and explore issues – important where this involves a sequence of, rather than

single events (Mahoney 1997). This was particularly valuable as it provided an opportunity to

view what was actually done (not simply documented or explained) and provided the

researcher with insight into participants’ communication with other individuals (Kendall &

Kendall 1988, p. 190). These observations also confirmed or contrasted findings from other

data collection methods (Kendall & Kendall 1988, p. 191). As noted by Miller and Crabtree

(1999, p. 15-16), this was a time-intensive and demanding method of data collection.

Observations in the hospital scenario were particularly important, as they revealed what

information was actually being used and how this was obtained, in contrast to information use

suggested by the participants at interview. This is in keeping with Mahoney’s (1997) opinion

that the ’observer is more than just an onlooker, but rather comes to the scene with a set of

target concepts, definitions, and criteria for describing events’. In this case it was to identify the

nature and sources of medication-related information that were used. For this exploratory

exercise the recording tool was essentially unstructured (Miller & Crabtree 1999, p. 15-16).

The researcher attempted passive rather than active observation to minimise observer

influence (Maciaszek 2001). However, it must be acknowledged that as a domain practitioner,

participants could have considered the researcher more as a ‘team’ member rather than

detached observer and therefore this could have brought about some behavioural changes in

participants.

3. 6.3.5 Use of focus groups Focus groups were important in this research project as natural interaction existed between

the two professional groups (GPs and accredited pharmacists) and it was valuable to obtain

their different perceptions of the information model and prototype. A focus group was also

thought to be useful in the evaluation of the document prototype by pharmacists with different

levels of experience in medication reviews. The usefulness of these focus groups in addition

to other techniques was that the group interaction would generate new data and understanding

unlikely to emerge without this interaction (Mahoney 1997) – particularly social contexts and

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important group dynamics (Mahoney 1997).

The approach used by the researcher to the focus group varied from that normally used.

Conducting a focus group would usually involve one or more moderator(s) who are there not

only to conduct the group, but also to help avoid biases that could be imposed on that group

by researchers (Kuzel 1999, p.119). However, with the notion that a ‘focus group is only as

good as its moderator’ (Kuzel 1999, p.120), the researcher decided to act as the moderator,

as his domain experience provided a particular level of understanding of hospital and

community pharmacy practice that could be used to stimulate discussion and improve the

quality of the data collection. However, understanding the problem of potential bias, the

researcher was clear in the intent to learn rather than to instruct (Sim 1998)

3. 6.3.6 DocumentsThis research project used purposive sampling (Kendall & Kendall 1988, p. 93) where one or

more examples of each type of medication-related document used by participants in decision

making were collected. This was useful in that documentation often provides insights into a

setting or group of people that cannot be observed or noted in any other way (Mahoney 1997).

Sampling included both public (e.g. reports, records) and personal (e.g. diaries, notes)

documents (Mahoney 1997). This required some documents to be de-identified to protect the

identity of patients and/or staff. Although there was a danger that these were incomplete,

documents provided an inexpensive and inconspicuous way of collecting data (Mahoney

1997).

3. 6.3.7 PrototypingPrototyping can be viewed from more than one perspective. It can be seen as a method used

to develop information systems (Middleton 1999) or a data-gathering technique (Kendall &

Kendall 1988, p. 219) – both occurred in this project.

Prototyping was used in Part 2A to test and refine the information and interface models through

user reactions and suggestions for improvement. The approach used to prototyping was not

the ‘traditional’ one of investigating options to determine the feasibility of a solution to a

problem (after elicitation of initial user requirements) (Pfleeger 1998, p. 169). Rather, it was

evolutionary (as opposed to exploratory and throw-away), intended to learn about a problem

and also used as part of the delivered (software) solution (Pfleeger 1998, p. 169). A rapid

prototyping approach is seen to be an advantage for developing expert systems where system

specifications are likely to change during the development (Bloom & Chung 2001), when there

is little previous design experience, the environment is uncertain or unstable, or decision-

making is unstructured or semi-structured (Kendall & Kendall 1988, p. 230). In addition, as the

HMR process is not a ‘highly-structured’ problem, it is a suitable problem for prototyping.

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Overall, prototyping matches the project domain well.

Prototyping can also serve as a basis for knowledge acquisition capturing smaller details that

are easily missed during requirements elicitation (Bloom & Chung 2001). This ability allowed

closer user participation and early feedback to the researcher that better reflected their real

world needs (Lenz & Kuhn 2004). This, in turn, was expected to lead to better acceptance

(Lenz & Kuhn 2004).

Prototyping in this project was also complementary to the chosen methodology, as DR is

underpinned by the construction of an artefact that can be used as an experimental proof of a

method or exploration of a method (or both) (Vaishnavi & Kuechler 2005).

Myers (2005) has suggested that in quantitative research, a clear separation between data

gathering and data analysis can be difficult (compared to quantitative research). The next

section therefore necessarily discusses data analysis as a follow-on from the data gathering

techniques in this section, to link but separate these activities.

3.7 Data analysisData analysis used a number of techniques, depending on the nature of the data and the

different aims within the project. This included modelling, prototyping, use of descriptive

statistics, content analysis and also a framework to evaluate the outcomes of the field study.

These are reported below.

3. 7.1 ModellingRevealing essential elements in relationship to one another (Friedman 2003) – in this case a

taxonomy of information components considered essential for medication management –

allowed the development of simple theory, rather than a dynamic model (describing process

or action) (Friedman 2003). As described in Chapter 2, the researcher was required to develop

an information model for medication as none were suitable for use within this project. However,

models in the health-care environment have been described for more complex tasks such as

clinical guidelines (Peleg et al. 2002), electronic health records (Beale & Heard 2003; Berg &

Toussaint 2003), clinical practice (Tange et al. 2003), business rules (Iyengar 2001) and drug

interactions (Solomon & Heathfield 1994). Many of these are commonly directed at building

blocks of medical knowledge or at the essence of medical decision-making (Berg & Toussaint

2003).

Modelling in the project proceeded through a number of iterations. Data from the hospital

scenario were analysed using QSR NUD*IST Vivo® (nVivo) version 2.0 software (Qualitative

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Solutions and Research Pty Ltd.) to form a preliminary qualitative model. The coding process

is described later under content analysis. This model was refined as a UML-based class

diagram to assist with hierarchical modelling, which also became the basis for the digital

document prototype. Subsequent refinements to the model after bench top testing and field

tests were incorporated into the UML model and document. A further intent was to ensure that

the information model was ‘aware’ of information flow – i.e. what information was relevant to

what user. However, this was not modelled explicitly but addressed by the context of

information use and implemented within the document.

3. 7.2 PrototypingAs alluded to earlier, evolutionary prototyping was used as method of data analysis to refine

the digital document prototype (and therefore the information model) from user interaction and

feedback. This was in line with the DR principles of ‘build... evaluate... learn’ (Rossi & Sein

2003). Prototype testing occurred in benchtop testing in Part 2A and in the subsequent field

trials in Part 2B. This iteration allowed the more specific information model relating to the

hospital scenario to evolve into one that incorporated features to support medication

management in the broader community setting.

3. 7.3 Descriptive statisticsThe statistics used in this project were largely descriptive and used to categorise data about

participants and findings in keeping with the qualitative data approach (Neely et al. 2002). This

relied on the use of nominal scales and on the researcher developing appropriate codes or

categories for behaviours, words, etc., to allow the use of some relative frequency distributions

(Morgan, Gliner & Harmon 1999). However, as statistical methods are fittingly chosen based

on what the question is and what the data ‘look like’ (Neely et al. 2002), the researcher used

comparative statistics opportunistically where the same variables were used across more than

one scenario, or pre- and post-data were available.

3. 7.4 Content analysisContent analysis is one form of semiotics where the fundamental idea is that words/signs are

assigned to conceptual categories and the frequency suggests their relative importance

(Myers 2005). This identification of key themes or categories depends on the process of coding

qualitative data (Coffey & Atkinson 1996, p. 27) through an interpretive process of describing,

organising, connecting, corroborating and representing the data (Miller & Crabtree 1999, p. 20-

24). How the data are organised also helps to answer the research question (Miller & Crabtree

1999, p. 20-24). Data were coded by the researcher using nVivo software after transcribed text

from questionnaires, interviews and work observations had been entered into the nVivo

software (again by the researcher). The approach to coding was consistent with the editing/

organising style of Miller and Crabtree (1999, p. 20-24) although the researcher’s domain

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knowledge assisted with the development of initial and emerging categories. This coding

served not only to ‘count’ (as in quantitative analysis) but as a ‘heuristic device’ for discovery

(Coffey & Atkinson 1996, p. 30).

The process of coding within nVivo involved the creating of links from selected (marked) text

in documents to nodes created in nVivo. An nVivo node is an object that can represent any

concept that users want to represent to (e.g. people, ideas, places, mental states). Nodes can

also be given attribute values and grouped in sets. The node trees created from the data

subsequently become the basis of qualitative models representing relationships between the

nodes – and used to form the preliminary information models.

3. 7.5 Evaluation of research goalsAs well as analysis of textual data, the evaluation of the project goals described for Part 2B

required the researcher to consider subjective concepts such as 'efficiency', 'quality' and

'safety'. While considering this, the Human-Organisation-Technology (HOT) Fit model

suggested itself as possible framework for the evaluation of the field studies (Yusof, Paul &

Stergioulas 2006). This framework was developed by Yusof, Paul and Stergioulas (2006) after

critical appraisal of existing Health Information System (HIS) evaluation studies. This model

contained dimensions of interest to this project (i.e. human and technology dimensions) and at

various levels described the goals for the field research – quality, efficiency and safety (clinical

outcomes). Further, this model also provided a mechanism for the evaluation of the interface

(the digital document artefact). The HOT Fit Model is shown as Figure 3-2 and elements of

evaluation suggested by Yusof, Paul and Stergioulas are shown in Appendix D.

One parameter of interest to the researcher was the ‘quality’ of home medication review

reports produced by the pharmacist for the GP. This could be assessed against a guideline

(the HMR Quality Assurance Form) developed as a quality assurance tool by the Southern

Divisions of General Practice (SDGP) and the Drug and Therapeutics Information Service

(DATIS) in South Australia. This guideline was used by accredited pharmacists as a ‘check list'

to determine the quality of HMR reports sent to the GP. This tool was an accepted and

pragmatic quality assurance tool that was highly relevant to pharmacists’ practice – and

therefore an appropriate tool for use in this research. This tool is shown in Appendix C.

This measure of quality was added to the list of Net Benefit evaluation items in the HOT Fit

Model.

The remaining question to be addressed in this chapter is (after question A, can medication

management-related issues in the hospital environment be resolved by the use of

technology?):

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This question has been left until the end of the chapter as it constitutes a significant topic of

discussion in its own right. Digital documents and the rationale for using this approach have

been discussed in Chapter 2; and the technology used to materialise the digital document is

described in the next section. As the health technology sector is also an area of significant

activity in regards to standards, standards with potential impact or applicability to the project

are also discussed.

3.8 Technology and Standards

3. 8.1 XForms The digital document artefact was implemented using a device-independent XML technology

called XForms. In contrast to HTML representations, XForms comprises separate sections

which describe what the form does and how the form looks, i.e. purpose and presentation,

allowing great flexibility (http://www.w3.org/MarkUp/Forms/, viewed 2006-01-05). Although a

recent standard, this offers considerable advantages because of platform independence, the

ability to develop forms to collect (XML) data, support for the structured interchange of data

and workflow, auto-filling and pre-filling of forms, and decoupled data, logic and presentation

(W3C 2004). Also, as a pivotal problem of medical data is the absence of machine-readable

structures, the document-oriented view of XML is seen to correspond well with the organisation

of health care data (Schweiger et al. 2005). Since this artefact is a ‘proof of concept’ rather than

Figure 3-2: The HOT fit model (Yusof, Paul & Stergioulas 2006)

HUMAN

Net Benefits

TECHNOLOGY

ORGANISATION

FitInfluence

InformationQuality

UserSatisfaction

Structure

Environment

System Use

System Quality

ServiceQuality

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a complete system; and there is a need to maximise flexibility and response in keeping with

the design research approach, XForms appeared to be a candidate approach. In addition, this

project will also serve to test the technology itself in a novel environment (the health care

domain) and suggest its suitability (or otherwise) to address these types of questions in this

domain.

3. 8.2 The impact of standardsThe advantages of standards and standardisation are well known and will not be discussed in

this thesis. However, it is important to restate that any technology-related research must be

aware of any standards which may affect its direction, or the ways in which the technology is

applied or implemented. This is particularly relevant for technology-related research in Health,

where there is significant interest in standardisation to improve communication, share data,

reduce cost, increase quality and improve outcomes. For example, in January 2005, 13 major

health and IT organisations in the United States (US) endorsed a ‘Common Framework’ to

support improved health information exchange (American Medical Informatics Association

2005).

The researcher undertook minor selective literature reviews to research emerging and/or

relevant technology standards for metadata, data representation and messaging. These

included XML Schema, the Resource Description Framework (RDF), Web Ontology Language

(OWL), HL7 messaging, openEHR, Clinical Document Architecture (CDA), archetypes, HL7

templates and Genre Taxonomy. Similar literature was also sought on discussions of

electronic guideline representations (e.g. GLIF, EON, Prodigy and GEM). The appropriate

standards initially seen to be relevant to the research project were XML schema, openEHR

and CDA. Genre and Pharmaceutical Care Network Europe (PCNE) (American

(Pharmaceutical Care Network Europe Foundation 2003) taxonomies were also investigated

for categorisation of concepts. CDA was seen to be particularly relevant in relation to the

intention of the digital document artefact; and this is discussed in the next sub-section.

3. 8.2.1 CDA/HL7The mission of the Health Level Seven (HL7) standards organisation is to create and promote

standards for the exchange, management and integration of electronic health care information

to increase the effectiveness and efficiency of health care delivery (http://www.hl7.org/about/,

viewed 2006-01-05). Enabling semantic interoperability across all platforms is a prime HL7

motivation (Dolin et al. 2001). The CDA was particularly relevant to this research project as it

is an XML-based document mark-up standard that specifies the hierarchical structure and

semantics of’ ‘clinical documents’ for information exchange (Liang, Bodorik & Shepherd 2003).

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A clinical document defined by HL7 has persistence, stewardship, potential for authentication,

wholeness, and human readability – and is defined as a complete information object that can

include text, images, sounds, and other multimedia content (Alschuler 2002). This approach

means that a XML document can at least be displayed at the recipient's site, using an

appropriate style sheet, and interpreted by a human, even if the contents of the document are

not ‘understood’ by the recipient's local system (Beyer et al. 2004). CDA document type

definitions describe data at three different levels of abstraction (Beyer et al. 2004) – CDA (at

Level 1) has been used to implement hospital discharge letters and summaries to

communicate information to the community setting (Paterson et al. 2002; Bludau, Wolff &

Hochlehnert 2003).

There are significant similarities between the CDA model and the intent of the digital document

in this research. In particular, this is the communication of clinical information, the use of XML

as an underlying representation and the importance of human readability. However, this

research emphasises an unrestricted approach to the information needs for medication

management, (i.e. without taking the HL7 Reference Information Model (RIM)1 as a starting

point). The focus of the project on human-to-human communication is also different from the

HL7 intent of supporting machine interchange. Therefore, the main differences are that CDA

intention is about communication (between systems) using XML schema and standardising

data representation with different granularities across its three levels. The approach with the

document metaphor is to communicate information to the human user, use the information

model to suggest the 'schema’ implicitly within the XForms model, and have different levels of

structure and granularity as suggested by the users to support appropriate decision-making.

The essential differences are initial intent rather than outcome (for the human user). However,

given the same underlying implementation technology, this does not preclude CDA

compliance in future work.

3. 8.3 User interface design‘Is it usable?’ – this is a question often asked about software (Weinshenk, Jamar & Yeo 1997,

p. xv). The research journey undertaken to formulate the information model and digital

document should in part answer this question, certainly from the perspective of the information

elements underpinning the medication-related decision process and their representation in the

digital document. However the user interface consists of a number of elements, such as

screens, windows, controls, menus and metaphors – the visual components that the user sees

and that affect how effective the user interaction will be (Weinshenk, Jamar & Yeo 1997, p. 7).

The goal here was to implement a well-designed interface that would reduce errors and make

people more productive as well as ensuring use (Weinshenk, Jamar & Yeo 1997, p. 7). The

1. The RIM is the source of information objects used in HL7 specifications

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principles for ‘intelligent interface design’ used in this project were taken from Weinschenk,

Jamar and Yeo (1997).

3.9 LimitationsThis research project has a number of limitations. The primary limitation results from it being

a sole researcher project. This potentially impacts on objectivity across a range of activities as

there is not a process to validate the reliability of interpretation or coding with other

researchers. This could have affected classification and/or coding within the literature review,

the qualitative coding used for model development; and direction chosen for development of

the digital document prototype. Similarly, as the sole recorder, moderator and interpreter of

questionnaire/interviews, work practices and focus groups, total objectivity was difficult

because of the researcher’s prior domain and personal experience. However, as the chosen

methodology (design research) is iterative and interactive through the artefact – it can react to,

and can change the direction of the research as knowledge of the problem increases

independently of the researcher – addressing some concerns about researcher bias. Further,

the project comprised only a small number of participants in both the hospital and community

scenarios – although data triangulation from a number of sources contributed to the validity of

the findings. However, the project is a proof of concept, intended to be further tested in

medication review field studies to validate the model and approach.

The chapter is summarised next in Section 3.10.

3.10 SummaryThis research project explored whether a digital document could be used to support decision-

making in health through a specific investigation of whether a digital document could be used

to support pharmacist decision-making in medication management. The need for the latter was

based on the researcher’s domain knowledge and was supported through examination of the

literature.

The digital document evolved in parallel with the development of an information model based

on data collection through an initial relatively information-rich hospital scenario to a more

general community environment. The methodological approach was empirical, with an

interpretivist, inductive stance using Design Research. The technology selected for

implementation of the digital document was XForms. The final aims were to investigate

whether this approach could improve the quality, efficiency and safety of the medication

management process in the community.

The next chapter discusses Design Research in more depth, in particular, its suitability for

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conducting research in complex and unstructured environments. From the foundations of its

use in education and IS, a case is made for its being an appropriate and novel method for

researching practice-based problems in the health care domain.

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Chapter 4

Design research in complex environments

4.1 IntroductionChapter 3 introduced methodology and candidate strategies to answer the research

questions; and concluded that Design Research was appropriate to use for a number of

reasons:

• the research environment was information-rich with ill-defined contexts

• there were complex interactions between problem and solution

• flexibility was required to allow changes to the processes and artefact

• there was a dependence on human cognitive abilities to produce a solution

• there was a dependence on human social abilities.

Similarly, the technology selected for implementation of the digital document was XForms,

based on the need to maximise flexibility and response in keeping with the Design Research

approach.

This chapter continues the discussion of Design Research (DR) and, in particular, its suitability

for research in complex and unstructured environments. This is approached from an

investigation of the use of DR in education and Information Systems (IS), with justification

made for it being an appropriate and novel method for researching practice-based problems

in the health care domain.


• it begins with Section 4.2 begins that considers the notion of design

• Section 4.3 discusses issues in dealing with complexity

• the use of Design Research in Education research is demonstrated in Section 4.4

• the use of Design Research in Information Systems research is demonstrated in Section

4.5

• the application of Design Research to the Health environment is justified in Section 4.6

• Section 4.7 discusses Design Research foundations

• the Design Research approach s aligned with the research plan in Section 4.8; and

• the chapter concludes with a summary in Section 4.9.

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4.2 Design – what’s in a name?Before DR can be discussed, it is useful to clarify terminology concepts identified in the (IS)

literature which may cause confusion. These are design, design theory, design science and

design research (DR) and, consequently, artefact.

Design is defined by the Merriam-Webster On-line Dictionary (http://www.m-w.com/cgi-bin/

dictionary, viewed 2006-06-26):

as a verb: ‘to create, fashion, execute, or construct according to plan’, or as a noun: ‘a plan or protocol for carrying out or accomplishing something (as a scientific experiment); also: the process of preparing this’

The design of artefacts has been carried out for centuries and distinguishes the sciences from

the professions (Simon 1996, p. 111; Vaishnavi & Kuechler 2005) such as engineering,

medicine, business and architecture (Simon 1996, p. xii). Most definitions of design share

three attributes: they refer to a process; the process is goal-oriented; and the goal is about

solving problems, meeting needs, improving situations, or creating something new or useful

(Friedman 2003).

‘Design ideal’ has also been described (at the most abstract level) where this describes the

values and standards which define the ultimate ‘good’ at which some design project aims – this

may be technical, economic or aesthetic standards, or a variety of other social ‘goods’ such as

equity, peace or conservation of natural resources (Klein & Hirschheim 2001).

Fallman (2003) presents three ‘accounts’ of design theory:

• the process-oriented conservative account (a linear process where every step is rational

and possible to describe)

• the product-oriented romantic account (guided by the designer’s values and tastes, such

as in poetry, drama, painting, sculpture and music); and

• the down-to-earth pragmatic account (a hermeneutic process of interpretation and

creation where designers interpret the effects of their designs in their settings).

Walls et al. (1992) consider Design Theory to be a package of three interrelated elements: a

set of user requirements; a set of system features (or principles for selecting system features);

and a set of principles deemed effective for guiding the development process. This can be

thought of as a complete package of guidance for designers (Markus, Majchrzak & Gasser

2002). Despite such formal guidance, however, there needs to be an unfolding ‘design

dialogue’ between the designer and customer that investigates the relationship between

details of the design and the problem to be solved (Fallman 2003).
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Design science has its origins in the ‘sciences of the artificial’ (Hevner et al. 2004), such as

architecture and engineering (McKay & Marshall 2005). This is a body of knowledge about

artificial (‘man made’ sic) objects and phenomena designed to meet certain desired goals

(Vaishnavi & Kuechler 2005). Design science is considered to be a systematic approach to

design, not just the use of scientific knowledge of artefacts.

Design itself, in some sense, can be seen as a scientific activity – although this is a

controversial concept challenged by many designers and design theorists (Cross 2002).

Nunamaker et al. (1990) classify design science as (applied) research which uses knowledge

to solve practical problems. It is technology-oriented and attempts to create things which serve

human purposes through the basic activities of building and evaluation (as opposed to natural

and social sciences, which try to understand reality) (Au 2001). Some comparisons made

between natural and design science enquiry (Lee 2000) are shown in Table 4-1.

Design science products are of four types – constructs, models, methods, and

implementations – but, absent from this list are theories, the ultimate products of natural

science research (March & Smith 1995). Fundamentally, from an IS perspective, design

science is about addressing business needs or problem-solving through constructing and

applying innovative IT artefacts to understand the problem addressed by the artefact and the

likelihood that this approach will provide a solution (Hevner et al. 2004).

There is some confusion in the literature, however, between the fields of practice and research

(Friedman 2003) on what constitutes design science and design science research (or DR) –

and the need to separate routine design (or system building) from DR (Hevner et al. 2004).

McKay and Marshall (2005) stress that the distinction between ‘designing’ (design science)

and ‘researching designing’ (DR) can be quite subtle; and more easily separated at a

conceptual level than at a practical level. Design researchers do not only design an artefact to

address a problem, but also conduct research into some aspect or dimension of the design

activity relevant to a particular problem. The process of design itself will add to knowledge, but

it is ‘the systematic and methodological enquiry into that practice’ that constitutes DR

Table 4-1: Comparisons of natural science and design science enquiry (Lee 2000)

The activity The purpose ExamplesNatural science enquiry Describing and explaining

nature and society.The description/explanation theory is true.

Physics.Biology.Economics.Psychology.

Design science enquiry Designing something new. The design is effective. Medicine.Architecture.Law.

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(Friedman 2003). In short, DR embodies the systematic acquisition of knowledge alongside

design and design activity (Bayazit 2004).

Thus, DR retains the goal of successful design but adds an additional goal of developing

useful, generalisable theories (Edelson 2002). However, Barab and Squire (2004) consider it

both critical and challenging to continually try to make two types of arguments for ‘experience-

near significance’ and ‘experience-distant relevance’, suggesting instead that the pragmatic

philosophical underpinning of DR is that the value of a theory lies in its ability to produce

changes in the world.

A further perspective on the ‘direction’ of design science is provided by McKay and Marshall

(2005) who identify a concern that DR is becoming narrowly framed with the pervasive view

that it is about ‘things’ of interest (e.g. decision support systems) or aspects of technical

systems (e.g. data models and CASE tools). This is in contrast to the view promulgated in the

Arts, where there is an attitudinal difference in definition:

design research regularly participates in the redefinition of the design process away from the stand-alone object and into the integrated system… By moving away from ‘mere styling’ of the product itself and into the interlocking systems that manifest, support, constrain and envelop products, designers can rightfully lay claim to a much farther-reaching contribution (McKay & Marshall 2005)

The central construct of DR – the artefact – is defined by the Merriam-Webster On-line

Dictionary (http://www.m-w.com/dictionary/artefact, viewed 2006-03-02) as: ’(1a) something

created by humans usually for a practical purpose’.

Simon (1996, p. 6) suggests that an artefact can be thought of as a meeting point ('interface')

between an 'inner' environment (the substance and organisation of the artefact itself) and an

'outer' environment (the surroundings in which it operates). If the inner environment is

appropriate to the outer environment, or vice versa, the artefact will serve its intended purpose.

There has been much discussion concerning what constitutes an ‘IT artefact’, seemingly

encompassing almost anything that is touched or affected by IT – suggesting a ‘boundary’

issue (Alter 2003b). Alter (2003b) suggests that this term – Benbasat and Zmud’s (2003)

definition – is too unclear to serve as a basic concept and better describes an ‘IT-reliant work

system’. The artefacts in this thesis are certainly IT artefacts, but the intended meaning here

is in line with the Dictionary definition above: ‘something created by humans usually for a

practical purpose’ – referring to the information model and its digital document implementation.

This section has discussed the various meanings associated with ‘design’ and introduced the

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artefact as being at a meeting point with the environment in which it will operate. A valuable

relationship in design is that understanding the design problem requires specific knowledge of

a domain; and designing a solution will lead to a further understanding of that domain

(Fitzpatrick 1998). DR can therefore be considered to be particularly appropriate for problem-

solving in complex environments; and this is introduced in the next section.

4.3 Dealing with complexityThe landmark article by Horst Rittel and Melvin Webber (1973) from UC Berkley, Dilemmas in

a General Theory of Planning, observed that there was a whole realm of social planning

problems which could not be successfully addressed by traditional linear, analytical

approaches (Ritchey 2005). These became known as ‘wicked problems’, as opposed to ‘tame

problems’.

Conklin (2001, p.11) in Ritchey (2005) defines a tame problem as one which:

• has a relatively well-defined and stable problem statement

• has a definite stopping point (we know when a solution is reached)

• has a solution which can be objectively evaluated as being right or wrong

• belongs to a class of similar problems which can be solved in a similar manner; and

• has solutions which can be tried and abandoned.

In contrast, wicked problems are ill-defined, ambiguous and can be associated with strong

moral, political and professional issues and, as they are strongly stakeholder dependent, there

is often little consensus about what the problem is, let alone how to resolve it (Ritchey 2005).

Further, wicked problems are sets of complex, interacting issues evolving in a dynamic social

context – and new forms of wicked problems can emerge as a result of trying to understand

and solve an existing problem (Ritchey 2005). Examples of important wicked problems include

complex, long-term social and organisational planning problems (Ritchey 2005), such as:

• what is a good national immigration policy?

• how should scientific and technological development be governed?

• how should we deal with crime and violence in our schools?

• how should an organisation develop in the face of an increasingly uncertain future?

Hevner et al. (2004) suggest that DR can address ‘wicked problems' through:

• the design of artefacts that embody complex interactions among subcomponents of the

problem and its solution

• allowing inherent flexibility to change design processes as well as artefacts

• acknowledging a critical dependence upon human cognitive abilities (i.e. use of

creativity) and human social abilities (e.g. teamwork) to produce effective solutions.

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The design problem can be characterised as a ‘wicked problem’ where understanding and

designing are part of both the problem and the solution (Fitzpatrick 1998). This approach is

particularly usefully for new areas or where there are deficiencies in existing systems (Rossi &

Sein 2003).

Markus, Majchrzak and Gasser (2002) noted that emergent knowledge-intensive processes

(EKP) have challenging information requirements as they involve tacit and explicit knowledge;

and general and contextual knowledge – as well as requiring expertise to apply this

knowledge. Further, because knowledge is distributed across experts and non-experts, EKPs

also require knowledge to be shared. The researcher believes that these problems typify the

knowledge intensive areas of education and health. Furthermore, as all disciplines build

knowledge bases, how they do this is important, because it reveals processes which offer

cases for design (Owen 1997). Nonetheless, understanding what cooperative work means and

how to design systems to support this work are problems which defy simple definitions and

solutions (Fitzpatrick 1998). The use of design theory within these areas may allow the

development process to be more manageable by restricting the range of development

practices for developers to a more manageable set (Markus, Majchrzak & Gasser 2002).

The fields of education and IS are well characterised by problems of a wicked nature and are

supported by appropriate evidence of the usefulness of DR in those areas. The next two

sections examine this evidence, first in education and then in IS. For each domain, the

discussion begins with some background to DS, the suitability and advantages of DR; and also

some issues which require consideration.

4.4 Design research in educationThe origins of DR in education can be found almost a century ago with the recognition of the

difficulty of studying complex human functioning found in classrooms.

Thorndike (1910) in O'Donnell (2004) noted that:

(the) extreme complexity and intimate mixture with habits in the case of human instincts prevents studies of them, even when made with great care, from giving entirely unambiguous and elegant results

DR in education was introduced against a backdrop of criticism about the use of laboratory

studies (e.g. studying the memory process) that used artificial materials, when those contexts

and materials were so different from the ones which students would actually use in a real world

setting (O'Donnell 2004).

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The application of scientific methodology in education was seen to be problematic (Hoadley

2004) as:

• all the possible variables could not be controlled

• studies could not be double-blinded

• an intervention in an educational setting was a dependant rather than independent

variable

• there was a blurring of researcher-participant distinction

• generalisation was tentative (there was no expectation of universality of results)

• the researcher frequently followed discoveries where they led

• there was a need to record not only the intervention and rationale for design, but also the

changes over time and how a particular representation embodied (or did not) the

hypotheses being tested.

The term ‘design experiment’ was introduced by Brown and Collins in 1992, but was replaced

by design research (or design-based research) as being more appropriate in light of the nature

of the process (it was not really an ‘experiment’) (O'Donnell 2004). ’Developmental research’,

a form of DR, has been in use in Europe for some years (Kelly 2004). Educational interventions

are viewed as holistic, involving interactions between materials, teachers and learners; and

since the intervention is a product of the context in which it is implemented, the intervention

itself is the outcome (or at least an outcome) (The Design-Based Research Collective 2003).

These partnerships can also help distinguish between a ‘lethal mutation’ – a reinterpretation

that no longer captures the pedagogical essence of the innovation – and a productive

adaptation which preserves this essence and tailors the activity to the needs and

characteristics of particular classrooms (The Design-Based Research Collective 2003).

The primary goal of DR in education is to ’investigate how different learning environment

designs affect dependant variables in teaching and learning’ (O'Donnell 2004). Educational

research which is removed from practice may not account for the influence of contexts, the

complex nature of outcomes and the incompleteness of knowledge about which factors are

relevant for prediction (The Design-Based Research Collective 2003). In other words, learning,

cognition, knowing and context are inter-related and cannot be treated as isolated entities or

processes (Barab & Squire 2004).

DR in education is founded on the notion that important things can be learnt about the nature

of learning by attempting to engineer educational innovation amongst children in everyday

settings (Bell 2004). In addition, complex educational interventions can reveal phenomena of

interest to study that will subsequently promote specific educational outcomes and develop

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new theoretical insights about the nature of learning (Bell 2004). Importantly, DR also allows

research findings to be derived through adaptive evaluation (Collins, Joseph & Bielaczyc

2004). This provides the opportunity to advance the understanding of teaching, learning and

educational systems at the same time (Edelson 2002).

Shavelson et al. (2003) in Joseph (2004) describe DR in an educational context as:

such research, based strongly on prior research and theory and carried out in educational settings, seeks to trace the evolution of learning in complex, messy classrooms and schools, test and build theories of teaching and learning, and produce instructional tools that survive the challenges of everyday practice.

Three important intertwined goals for DR projects can be inferred from this definition –

research, design and pedagogical practice (Joseph 2004).

Edelson (2002) states that the objectives of DR (novelty and usefulness) are different from

traditional empirical research and thus this form of research should not be judged by the same

standards as ‘scientific method’ based research. The point of DR is to generate theories which

could not be generated either by isolated analysis or by traditional empirical approaches. The

blending of research and practice also fits well with the purposes of education, given its

fundamentally interventionist nature – without empirical research, it would be difficult to make

theoretical or practical progress in natural settings and refine use-centred theory (Bell 2004).

Further, because education is by nature an interventionist, designed endeavour, the scope of

DR may continue to expand and prove to as be productive as other established modes of

educational enquiry (e.g. experiment, historical, philosophical, anthropological or sociological

research) (Bell 2004). However, DR can still incorporate outcome-based evaluations which

characterise traditional theory testing (Edelson 2002), although traditional before-and-after

testing is less meaningful (Hoadley 2004).

The conventional role of design in educational research has been as a strategy for testing

theories – which assumed a fully developed theory that mapped directly into design (Edelson

2002). However, with an increasing concern for research to be educationally relevant and to

contribute to improvement (O'Donnell 2004), recent literature describes DR as a process

where design plays a critical role in the development of theories – not just evaluation (Edelson

2002). Kelly (2004) suggests that DR’s contribution is primarily its input into the thinking of

other researchers in similar contexts, who can take the foundations and use other

methodologies to allow generalisation. In fact, Kelly prefers the use of ‘working words’ such as

hypothesis, conjecture, model, framework, belief, rationale (amongst others) to ‘theory’, which

in science means a ‘well-substantiated explanation of some aspect of the natural world that

can incorporate facts, laws, inferences, and tested hypotheses’ (Kelly 2004).

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In DR, hypotheses about the learning phenomena are embodied in the designed artefacts

(Joseph 2004). Theory development often begins with an initial (incomplete) set of hypotheses

to guide the design process which progressively constructs a coherent theory – through a

parallel and retrospective process of reflection on design experiences and outcomes (Edelson

2002). However, a search guided only by the most general heuristics of 'interestingness' or

novelty can be an equally suitable mechanism for finding a suitable model for a social design

process (Simon 1996, p. 162).

As with many other research approaches, identification of gaps in the research literature can

originate questions (Joseph 2004). Consequently, design work is guided by the knowledge of

these gaps in current understanding to focus effort in areas which will make a useful

contribution (Edelson 2002) – empirical refinement can then identify results which can not only

lead to improvement of a particular learning design, but also to refinements in learning theory

itself (O'Donnell 2004).

O’Donnell states that the selection of questions in this domain should be those having a

meaningful relationship with student learning (O'Donnell 2004). Joseph (2004) agrees that

effective research requires a focus on specific questions – however, there are many design

considerations and there is a need to understand a large number of phenomena and variables

to improve a design. Thus, real-world practice and day-to-day needs do place constraints and

demands on design and research activities. Nevertheless, DR can use these design needs

and contextual demands as a way of determining the specific key questions of interest (Joseph

2004). Joseph (2004) asserts that there are some design questions which are critically

important – how are the artefacts used, how are they implicated in learning; and how might

they fail? A further issue is that, although design decisions (made within constraints) represent

opportunities for learning, they also provide a potential for researcher bias (Kelly 2004). Kelly

(2004) considers there is an association of ‘the contingent’ (parts that are more arbitrary) and

‘the necessary’ in these decisions; and that the real challenge is to connect the contingent to

the necessary.

A significant argument for DR is the usefulness of its results. If the ultimate goal of educational

research is the improvement of the education system, then results which directly address the

design of activities, materials and systems will be the most useful (Edelson 2002). The twin

goals of developing effective designs and contributing to basic understanding created through

the interactions of these goals is a ‘powerful engine for driving innovative work’ in education –

and because this takes place in a real-life context, design choices and research are closely

associated with that context (Joseph 2004). In fact, DR is something which: ‘might develop into

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a force sufficient to accelerate the ponderous educational system’ (Hake 2004).

There remain some key concerns and issues relating to DR in education:

• the relative certainty of its findings in comparison to traditional empirical research, as

explanatory power will be grounded in specific experiences rather than in statistical

methods (Edelson 2002)

• the ‘Bartlett effect’ – a tendency to select data that confirms the researcher's

expectations – particularly when portions of transcripts/interviews are selected to

illustrate a theoretical point, or when descriptions are selected from a large number of

potential examples. This risk is exacerbated by the amount of data collected (often too

much) (O'Donnell 2004)

• absence of standards for identifying when a design can be executed, should be

abandoned, or is promising enough to warrant exploration. The possibility of endless

revisions also has important resource implications for classrooms, curricula and

students' time (O'Donnell 2004)

• the question of when and how summative evaluation begins (Joseph 2004)

• problems with generalisation since relatively few participants are typically involved in

very in-depth analyses (Joseph 2004; O'Donnell, 2004)

• problems with generalisations across contexts (different schools, tools or circumstances)

(Joseph 2004) as complexity makes it difficult to identify contributors to success

(O'Donnell 2004)

• the context itself is not ’natural’ as it represents the joint efforts of researchers, teachers,

students and others who typically may not work so closely (O'Donnell 2004)

• the need to understand the role of the individual teacher, i.e. which aspect of activity

design and instruction belong to the model and which are due to the preferences of the

individual teacher (Joseph 2004)

• how to apply a useful model to new teachers and schools (Joseph 2004)

• the problem of managing large data sets produced by the DR process (Collins, Joseph &

Bielaczyc 2004).

DR in the educational setting has been employed in the fields of developmental psychology

(socio-cognitive development), cultural psychology, linguistic or cognitive anthropology; and

ethnography (Bell 2004). The focus of design efforts has varied with the interests of the

educational research community and has included design of curriculum, software, professional

development, school organisations, school-community collaborations (Edelson 2002); and

physics education (Hake 2004).

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The Design-Based Research Collective (2003) sees a number of prospects for Design

Research in education:

• exploring possibilities for creating novel learning and teaching environments

• developing theories of learning and instruction that are contextually based

• advancing and consolidating design knowledge; and

• increasing the capacity for educational innovation.

In summary, in education, design research activities are iterative, interventionist (innovative

and design-based) and theory-oriented enterprises whose theories do real work in practical

educational contexts (Cobb et al. 2003).

The use of DR as a research method in education ocurred in parallel with its use as a research

method in IS – this is discussed next in Section 4.5.

4.5 Design research in information systemsThe explorations of IS – unlike those of computer science (CS) and software engineering (SE)

which are often performed within the rules and practices of mathematics – usually occur in an

organisational (and therefore behavioural) context; and are based on relevant theories often

extracted from other disciplines (Glass, Ramesh & Vessey 2004). Although positivist science

shaped the field of IS in the 1980s, interpretive and critical science emerged as milestones in

the 1990s (Lee 2000). Lee (2000) considers that the IS research field has matured to the point

where substantive and methodological rigour make it the equal of any other business-school

discipline.

The prime focus of IS experts is on aligning IT artefacts within the organisational and social

contexts of use (i.e. the people who use them) – and on the implementation, evaluation and

consideration of related changes of these artefacts (Iivari, Hirschheim & Klein 2001).

However, some consider that the IS field has not deeply engaged its core subject matter – i.e.

the IT artefact (Orlikowski & Iacono 2001). One reason given is that IS researchers do not build

IT artefacts as most are not trained to do so (and so do not have the needed skills); and most

build their skills and experience around evaluating, theorising, and justifying existing artefacts

(Au 2001). There has been a call for more IT-reliant work in the IS field – with a greater

engagement with IT artefacts – as they are integral parts of work systems and therefore should

not be ignored when work systems are studied as systems (Alter 2003a).

The Conference on Design Methods held in London in 1962 (Jones and Thornley, 1963) is

generally regarded as the event that marked the launch of the design methods movement and

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design methodology as a field of enquiry in IS. A subsequent conference on the ‘design

method’ held in Birmingham in 1965 related 'the design method' to 'the scientific method' with

consequent reference to 'design science' (Cross 2002). Simon then further extended the

concept of design science in The Sciences of the Artificial published in 1969 (Lee 2000).

Lee (2000) considers that ‘design science is an old lesson just waiting for us to apply it’.

However, whereas natural science tries to understand reality, design science attempts to

create things which serve human purposes. It is technology-oriented, and its products are

assessed against criteria of utility or value – does it work, or is it an improvement? (March &

Smith 1995). This approach is particularly usefully for new areas where there are theories

which cannot be tested; and where there are identified deficiencies in existing systems (Rossi

& Sein 2003). Design is a key activity in fields such as architecture, engineering and urban

planning, which may not be thought of as ’sciences’ per se (March & Smith 1995).

Lee (2000) suggests that DR (or design science) contributes to resolving three dilemmas

facing IS:

• rigour vs. relevance

• reference vs. independent discipline in the development of the IS field; and

• technology vs. behaviour.

The first dilemma is addressed by DR’s application to real world problems, the discipline issue

is addressed by taking a system approach (therefore strengthening the notion of discipline

independence); and the latter through DR’s approach of treating the computer and behavioural

‘subsystems’ as being inseparable.

Purao (2002) does extend the concept of DR in IS to that of a paradigm. This is based on the

notion that DR creates new realities by ‘knowing through making’, something not anticipated

by the traditional philosophy of science. However, this discussion in this thesis will proceed

with the more conventional understanding of DR as a method.

From an IS perspective the main goal of DR is fundamentally about addressing business

needs or problem-solving (Hevner et al. 2004). Hevner et al. (2004) suggest that DR

addresses ‘wicked problems’ in IS characterised by:

• unstable requirements and constraints based upon ill-defined environmental contexts

• complex interactions among subcomponents of the problem and its solution

• inherent flexibility to change design processes as well as design artefacts

• a critical dependence upon human cognitive abilities, i.e. creativity, to produce effective

solutions

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• a critical dependence upon human social abilities (e.g., teamwork) to produce effective

solutions.

The challenge of designing decision support systems perhaps provides a good demonstration

of the wicked problems described by Hevner et al. – and it is not surprising that DR has been

used in the investigation of decision support systems (Arnott 2005).

DR begins with a perceived need which can originate in practice or be discipline-based (Purao

2002); and the IS field is particularly concerned with research and practice about problems and

solutions resulting from interactions between technology and (human) behaviour (Lee 2000).

In contrast to the natural science approach that aims at understanding phenomena, DR sets

out to develop ways to achieve human goals (March & Smith 1995) – DR researchers do not

believe that the 'truth' is 'out there', but help to create it through the generation of artefact

(Purao 2002). Lee (2000) believes that IS is about ‘technology-behaviour interactions’ rather

than ‘technology vs. behaviour’, i.e. they are inseparable. Similarly, as IS is viewed as a socio-

technical system (Sutcliffe 2000; McKay & Marshall 2005), the essence of IS lies in the

‘contextualisation of the machine in the social system’ and what makes DR resonate with

practice is its sensitivity to that social context (McKay & Marshall 2005).

The process of DR in IS involves the construction and application of innovative IT artefacts

which attempt to understand the problem addressed by the artefacts and the likelihood of this

approach providing a solution (Hevner et al. 2004). Artefacts can be expressed as constructs,

models, methods and instantiations or implementations (Au 2001; Vaishnavi & Kuechler

2005). As well as artefacts serving as models that represent situations as problems and

solution statements (March & Smith 1995), artefacts as ‘situated implementations’ can reveal

the knowledge to accomplish these solutions and then build theories about the problem and

solution (Purao 2002).This supports the beliefs of Morrison and George (1995) that the

dynamics of computer-based interventions cannot be understood unless we develop the

products that provide those interventions.

The interventionist, iterative cycle that underpins DR allows a prototype to serve as a system

specification or ‘evolutionary working system’ that can test an existing theory (Morrison &

George 1995); and become the basis for a new theory and new constructive intervention

(Vaishnavi & Kuechler 2005). However, although theorising about the IT artefact is intended to

uncover characteristics that are unique to IT, where IT artefacts significantly affect the task or

the environment, it can be beneficial to adapt theories from referent disciplines (March & Smith

1995).

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To return to the notion of truth, March and Smith (1995) suggest that the truth is essentially

what works in practice. As the implementation of an information system serves some human

interest, design choices will require value judgements and therefore necessarily select some

interests over others – this entails addressing what is ‘good’, ‘bad’, ‘right’ or ‘wrong’, as well as

technical issues about design (Klein & Hirschheim 2001). McKay and Marshall (2005) note that

concomitant people, processes and organisational structural changes are just as important

and relevant to improving a problem situation as a designed technical artefact. Consequently,

allowing the design process to capture the value judgements contained in organisational

decision-making and allowing them to be addressed rationally is important –- ignoring them

may not only be undesirable, but also may impose opportunity costs (Klein & Hirschheim

2001).

The DR approach also proposes a more realistic approach to the evaluation of systems. Simon

(1996, p. 28-29) talks about ‘satisficing’ where real world complexity means that the ‘best

answers’ to questions are unknowable; and since real world optimisation (with or without

computers) is impossible, a 'good enough' alternative is acceptable, not because this is

preferred but because there is no choice.

March and Smith (1995) however, identify a number of implications for IT research using

artefacts:

• there may not be an underlying deep structure to support a theory of IT per se so that

theories may need to be based on other theories of the natural phenomena (i.e. people)

that are impacted by the technology

• artefacts are perishable and consequently, so are the research results. As needs

change, therefore, the artefacts produced to meet those needs must also change

• as artefacts are being produced at an ever increasing rate, this results in innumerable

phenomena to study.

There is also a practical dilemma of competing design ideals – which design (ideal) should be

adopted, since development cannot be impartial and once the design ideal is made explicit,

development work is then bound by interest (Klein & Hirschheim 2001).

The suitability of DR for research in complex and unstructured environments is now discussed

in the context of the domain of interest for the research project – the health domain.

4.6 Designing a better health technology interventionDR has been discussed up to this point in relation to its suitability to address practical issues

and provide solutions in complex environments characterised by ‘wicked problems’ –

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education and IS. This research sought to apply DR in a new problem context in the health

domain – specifically, the problem of technology support for medication management. This

section describes the nature of the health care domain as a background for this decision; and

justifies the use of DR as appropriate and relevant for investigating a technology intervention

in this domain.

Health professionals work in an increasingly complex area characterised by advances in

medical science and technology, increasing specialisation, ever-greater patient expectations,

and, above all, the sheer size and diversity of health service provision (Pope & Mays 1995).

The interaction space within which clinicians carry out their work is also complex as individuals

must execute their tasks by communicating across rich social networks (Ash, Berg & Coiera

2004).

Information Systems in the health domain play an important role in improving health care

quality (Beyer et al. 2004). IT is seen as a valuable tool to provide productivity gains, cope with

demand, make health care delivery more consumer focused (European Commission 2004);

and address issues of quality and safety (Bates & Gawande 2003; Electronic Prescribing

Initiative 2004). IT plays a particularly significant role in information management (Sowerby

Centre for Health Informatics 2000), electronic prescribing (Electronic Prescribing Initiative

2004), clinical decision support and medication safety (Roughead & Semple 2002; Bates &

Gawande 2003). Safe care now requires a degree of individualisation that is becoming

unimaginable without computerised decision support (Bates & Gawande 2003) – information

systems are increasingly seen as an integral part of the health care process, rather than just

a tool (Beyer et al. 2004). However, health care processes are subject to change and health

information systems must be capable of adapting to this change where the driver for change

should be the need for the process improvement rather than the technology itself (Lenz et al.

2005).

Plummer (2001) describes Health Informatics (HI) has having ‘been concerned primarily with

the use of technology for the optimal use of health-related information for decision-making and

problem solving to improve health care outcomes’ – this term will be used in this thesis with

the same understanding. There are many similarities between the areas of HI and IS. Both are

multi-disciplinary fields. IS builds on reference disciplines including organisational theory,

decision science, information technology, and other management sciences – HI is also a blend

of referent disciplines including, but not limited to: psychology, sociology, anthropology,

organisational behaviour and management sciences (Plummer 2001).

HI and IS also face similar organisational issues when considering people and technology,

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including elements of power relationships, as well as politics and resistance – both share an

overall focus of successfully integrating people and technology to improve outcomes and

performance – both also share high failure rates in terms of information systems (Plummer

2001). Issues around health care, however, could be described as more information intense,

more organisationally complex, more turbulent, more paradoxical, more subjective; and more

emotionally charged than other industries and businesses (Plummer 2001).

Experiential knowledge is extremely significant in the practice of health professionals (e.g. in

medicine) – termed ‘knowledge work’ by Iivari, Hirschheim and Klein (2001). Such knowledge

work is differentiated from other work by: a body of knowledge; representations of the objects

of work; a deep theoretical understanding of the objects of work; and results which entail

knowledge as an essential ingredient (Iivari, Hirschheim & Klein 2001). Further, the complexity

of human behaviour within such environments is a reflection of the environment itself (Simon

1996, p. 80). The types of issues experienced in health clearly supports their classification as

‘wicked problems’ (Ritchey 2005) – similar to issues experienced in the fields of education and

IS. Subsequently, the researcher believed that a similar role existed for artefact-mediated

interventions – using design research – to produce effective problem solutions.

As with IS, socio-technical is a term also applied to the health system (Runciman & Moller

2001). The health system involves complex interactions between consumers, health

professionals and the health system framework itself (Runciman & Moller 2001). This

advocates for the use of IS research approaches that employ human-centric analyses of the

impact of computer systems on people; and consider how technology can be designed more

effectively for people (Sutcliffe 2000). However, the complexity of socio-technical evolution

should also never be underestimated (Lenz et al. 2005). Ash, Berg and Coiera (2004) caution

that when technologies become an integral part of health care work practices, behaviours

emerge out of the socio-technical coupling; and the behaviour of the overall system in any new

situation can never be fully predicted from the individual social or technical components.

Health information systems, as an integral part of these complex socio-technical systems,

must also cope with changing conditions and requirements (Beyer et al. 2004). The report of

the National Electronic Decision Support Taskforce referred to the need to investigate socio-

technical barriers which existed for health care providers and were preventing the uptake of

decision support systems (National Electronic Decision Support Taskforce 2002, p. 90).

Plummer (2001) identifies common organisational aspects that are critical to a system’s

success suggesting that these are critical in both IS and HI:

• organisational leadership and commitment

• the establishment of an appropriate coordinating body or mechanism

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• adoption of participatory approaches to IS development; and

• an iterative approach to development.

Some comparative dimensions of DR in education and IS have been synthesised from the

literature by the researcher; and summarised in Table 4-2. It is clear from this table that there

are many similarities in the approaches and problems encountered by researchers in both

domains. One of the curious elements of DR investigations is the parallel – but quite separate

– activities of these two groups of researchers over a comparatively long period of time. Table

4-2 also includes the equivalent DR dimensions for health, proposed by the researcher, based

on literature and domain knowledge – this summarises the reasons why DR methods are

appropriate for use in the HI environment.

Because of its applied nature, much research in the health environment is driven by specific

practical problems that are converted into research questions – rather than being derived from

the researcher’s theoretical perspectives (Pope & Mays 1995). Until recently, HI research has

tended to focus on the technical development of clinical systems and favoured the positivist

approach of medically trained researchers (Plummer 2001). But, as health care deals with

people, there is a whole set of questions about human interaction – and experimental and

quantitative methods are less suited to answer these questions (Pope & Mays 1995). It is this

complexity and subjectivity which supports the need for appropriate qualitative methodologies

for research and theory building in HI to improve success (Plummer 2001).

In summary, there are many parallels between the research in IS and HI in terms of the

organisational and information issues – although these two areas may differ in the degree of

intensity and ‘ways of knowing’ (how the discipline knowledge is evolved) (Owen 1997). It is

reasonable to assume, therefore, that the same research methods are appropriate to build

theory and improve practice in both. The issues of complexity and context addressed by DR

in educational research are also relevant to HI research – the DR approach in the present

research project clearly supports its interventionist nature as well as its desire to use scenarios

as test beds for innovation (Cobb et al. 2003). The DR approach – in particular, the DR cycle

and outputs – is outlined in the next section.

4.7 Design research foundationsIn keeping with the approach in Chapter 3 (Methodology), the discussion of DR will begin with

a philosophical perspective and then introduce the ontological and epistemological stances.

Sub-section 4.7.1 discusses the DR cycle in detail with outputs discussed subsequently in

Sub-section 4.7.2.

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Prior to this discussion, however, it is appropriate to provide an overview of DR – this is well

summarised by Vaishnavi and Kuechler (2005) in Figure 4-1, which shows the iterative nature

DR with process steps and associated outputs, as well as the knowledge flows which

contribute to understanding and theory development.

The DR approach uses qualitative and exploratory techniques through the development and

Table 4-2: Dimensions of DR in education, IS and health

Education Information Systems HealthBackground Teachers, students in complex,

'messy' classrooms and schools.

People, business, organisations and their existing or planned technologies, and work systems. Socio-technical systems.

Health professionals, support personnel, health consumers. Socio-technical systems. Substantial communication and distribution of general and local knowledge. Emergent knowledge processes.

Pre-emption Informed by prior research or incomplete theories.

Exploration of 'wicked problems'.

Exploration of 'wicked problems', related to quality, efficiency and safety.

Goal Test and build innovative theories / models of teaching and learning, and produce instructional tools that survive everyday practice.

Technology-based solutions to solve problems and improve performance of activities.

Solve problems of quality, efficiency and safety in the delivery of health care.

Artefact embodiment

Embody theory about learning phenomena in real-world context.

Define ideas, practices, technical capabilities and products and solutions.

Model or define practices, guidelines and processes.

Artefact expression

Activity structures, institutions, scaffolds, curricula, software, professional development, school organisations, school-community collaborations or conceptual frameworks.

Construct, model, method or instantiation. Software or hardware.

Construct, model, method or instantiation. Not necessarily technology-based.

Search process

Team needs to have collective expertise to accomplish the functions associated with developing design, conducting the experiment, and systematic retrospective analysis.

Requires domain knowledge. Explicitly represents only a subset or simplification of problem.

Requires domain knowledge. Explicitly represents only a subset or simplification of problem as much decision-making requires contextualisation and use of tacit knowledge.

Evaluation Improvement in value of a particular designed artefact or a process for carrying out design. Using methods able to document and connect learning processes with learning outcomes.

Typically 'satisficing' in light of practical constraints. Functionality, completeness, consistency, accuracy, reliability, fit with the organisation, and other relevant quality attributes.

Judged on perceived utility and impact on individuals and organisations. Notion of improvements in quality, safety and efficiency are important. Metrics from IS applied as appropriate.

Theory Theories of learning and instruction that are contextually based.

Predict or explain phenomena with respect the artefact's use. Knowledge represents operational principles.

Contribution to thinking of other researchers in similar contexts. Knowledge representing operational and decision-making principles / processes.

Relevance Theories of learning and instruction that are contextually based.

In respect to constituent community.

Contextually based.

Research outcomes

Novel learning and teaching environments and ultimately improvement of the education system.

Novelty, generality and significance of the artefact / solving an important previously unsolved problem.

Significance of artefact in solving problem / addressing issue, and ultimately improving delivery of health care.

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design of artefacts (systems and models) (Rossi & Sein 2003).

The ontological and epistemological standpoints for DR suggested by Rossi and Sein (2003)

are realist – the real world exists but we are not seeking it – but we can intervene in the world

to improve it. There are two general aspects of the realist view, existence and independence.

The realist claims that everyday life provides us with a familiar (and mundane) empirical

dependence on objects and their properties – but there is no further sense in which everyday

objects and their properties are dependent on anyone's linguistic practices or conceptual

schemes (Miller 2005).

Ontology for DR is evolutionary and complementary – an evolving artefact gradually takes

shape and becomes an object in the world – then, as the phenomenon of interest takes on

characteristics of the artefact, the changed version of the phenomenon assumes an emergent

ontological stance complementing the realist stance of the artefact (Purao 2002).

Epistemology in DR is ’knowing through making’, rather than truth through seeking; and the

stance can be described as reflective and hermeneutic (Purao 2002). It is reflective, since DR

moves between the phenomenon and artefact (generating data and theory), a cycle which

involves the gradual bridging of the gap between need and artefact (resonating with an action-

oriented view) (Purao 2002). As DR arrives at an understanding of the artefact and the

phenomenon at the same time, creation and understanding become part of the same

Figure 4-1: The Design Research cycle (Vaishnavi & Kuechler 2005)

Knowledge Flows Process Steps Outputs

Awareness of Problem

Suggestion

Development

Evaluation

Conclusion

Proposal

Tentative design

Operation and Goal Knowledge

Circumscription

Artefact

Performance measures

Results

Design Research Cycle

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epistemological process and cannot be separated (Purao 2002).

As DR researchers deepen their understanding of the phenomenon during their investigation,

it is important that they generate a comprehensive record of the ongoing design process and

the variety of data sources which may influence it (Cobb et al. 2003). For this reason, DR

typically triangulates multiple sources and kinds of data (connecting intended and unintended

outcomes to actions) in the pursuit of validity (The Design-Based Research Collective 2003).

However, the study of complex phenomena precludes complete specification of everything

that happens (Cobb et al. 2003), consequently it is important to distinguish between elements

which are the target of investigation and those which may be incidental, accidental or assumed

as background conditions (Cobb et al. 2003). This was an issue in the present research

project, as the artefacts under investigation could have been ‘muddied’ by participants’ desire

to include elements to ensure business needs were accommodated or only minimally

disrupted. The notion of maintaining a sense of central and incidental requirements was central

to the methodology (Cobb et al. 2003).

The Design-Based Research Collective (2003) proposes that good design-based research

exhibit the following five characteristics:

• the central goals (in an educational setting) of designing learning environments and

developing theories of learning are intertwined

• development and research take place through continuous cycles of design, enactment,

analysis, and redesign

• research on designs must lead to shareable theories which help communicate relevant

implications to practitioners and other designers

• research must account for how designs function in authentic settings; and must not only

document success or failure but also focus on interactions which refine understanding of

issues involved

• development of accounts relies on methods which can document and connect processes

of enactment to outcomes of interest.

This overall DR approach is now enlarged upon in the following two sub-sections, the design

research cycle and outputs of design research.

4. 7.1 The design research cycleThe DR cycle, the fundamental iterative approach of the DR method, describes the process

steps in the design science cycle as: awareness of problem, suggestion, development,

evaluation and conclusion (Vaishnavi & Kuechler 2005). These steps have also been

described as: identify a need, build, evaluate, learn and theorise (Rossi & Sein 2003). There

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is a fundamental concept there – the ability of the design researcher’s philosophical

perspective as progress is made through the phases. For example, if the design researcher

creates a reality through constructive intervention, s/he reflectively become a positivist

observer recording the behaviour of the system – the observations can then be interpreted to

become the basis for new theorising and a new, interventionist cycle begins – similar to action

research methodology (Vaishnavi & Kuechler 2005).

DR often begins with an early version of a design placed in a real-life context (Joseph 2004),

with that design typically evolving as the designers deepen their understanding of the design

context through analysis and formative evaluation (Edelson 2002). This process has been

described as akin to prototyping in software engineering (Joseph 2004). The design process

is thus a sequence of decisions made by the researcher to balance goals and constraints

regarding how the design process will proceed, what needs and opportunities are addressed;

and what form the resulting design will take (Edelson 2002).

There is also a stress on circumscription – an essential part of this methodology – which

assumes that each fragment of knowledge is valid only in certain situations, based on the

detection and analysis of contradictions, i.e. the researcher discovers when things don’t work

‘according to theory’ (Vaishnavi & Kuechler 2005). This does not happen because of a

misconstruction of the theory, but because of the inevitable incompleteness of any knowledge

– when the design process is forced to consider the problem in this way, valuable knowledge

is contributed to the understanding of the theories which motivated the original design

(Vaishnavi & Kuechler 2005). This iterative design process is thus seen as having two faces –

a prospective face (designs are implemented with a hypothesised learning process) and a

reflective face (design experiments are conjecture-driven tests) (Cobb et al. 2003).

The DR cycle raises an interesting issue of validity versus credibility. Hoadley (2004) states

that the concept of alignment is important to validity in DR – having the same individuals carry

ideas (theories) and intervention through explanation, prediction, falsification and application

ensures theories have practical application as a result of methodological alignment. In

contrast, when researchers are also the designers of the intervention, this can raise issues of

credibility (O'Donnell 2004; Barab & Squire 2004) because such interventions might be seen

to ‘taint’ the research context (Barab & Squire 2004). O’Donnell (2004) believes that the

iterative nature of DR can satisfy some of the issues of credibility (e.g. external comparisons,

replication, relationship between intervention and outcome; and ruling out alternative

explanations) – although this satisfaction is limited and objectivity is not really possible

(O'Donnell 2004). However, according to Cronbach (1982, p.108) in Bell (2004): ’validity is

subjective rather than objective: the plausibility of the conclusion is what counts. And

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plausibility, to twist a cliché, lies in the ear of the beholder’; and the: ‘truth essentially is what

works in practice’ (March & Smith 1995).

The main goal in DR is thus systemic validity (studies must inform theories which must inform

practice) rather than measurement validity (interpretation of the results accurately reflects the

truth of the theory being examined) (Hoadley 2004). Barab and Squire (2004) suggest that DR

offers a mode of enquiry which embraces consequential validity but while demonstrating this

local consequence and utility is necessary, it is not sufficient and theoretical assertions must

be made to go beyond the local context (Barab & Squire 2004). Cobb et al. (2003) also

consider that DR should investigate situations which can inform a broader class of

phenomena. This was in keeping with intention of the research project where the researcher

was investigating a specific medication-related case in health, but also had the intention of

informing just such a technology application to health in general.

The outputs of design research are discussed next, in Sub-section 4.7.2.

4. 7.2 Design research outputsDR outputs according to Vaishnavi and Kuechler (2005), include: proposal, tentative design,

artefact, performance measures; and results (assuming that some goal is achieved) – shown

in Figure 4-1. These outputs correspond to relevant and equivalent processes in the DR cycle.

March and Smith (1995) in Hevner et al. (2004) offer only two design processes but four design

artefacts. The two processes are ‘build’ and ‘evaluate’; and the artefacts are constructs

(vocabulary and symbols), models (abstractions and representations), methods (algorithms

and practices) and instantiations (implemented and prototype systems). Of interest, is that

Vaishnavi and Kuechler (2005) also make an analogy between the development of better

theories (as an output of DR based on artefact construction) to the outputs of experimental

natural science. Figure 4-2 shows an alternative view of DR outputs adapted by Purao (2002).

The main value of Purao’s model is that it shows how the artefact (as a situated

implementation) feeds back to knowledge (as operational principles) which in turn informs

emergent theory – the DR process as a mechanism for feedback. Purao demonstrates this by

means of a data retrieval example taken from Krishnan et al. (2001). The outputs of the

research project are also accommodated by this model – the situated implementation of the

digital document feeds back to knowledge articulated by the information model and the

XForms model; and these in turn fed back to the emergent theory of how medication

management could be supported by a digital document.

March and Smith (1995) state that theorising about instantiations may be also be viewed as a

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first step toward developing more general theories (e.g. explaining how electronic mail affects

communication may lead to more general theories of the effects of technology or more general

theories about human communication) or as the specialisation of an existing general theory

(March & Smith 1995). The research contribution lies in the novelty of the artefact and in the

persuasiveness of the claims that it is effective, e.g. a ’significant improvement’, or more

comprehensive or better performance (March & Smith 1995).

One notable limitation of this approach is that the technologies used to build artefacts are

perishable.The greater is the contribution of technology to the artefact, the weaker will be the

contribution of the artefact. Instead, the research it must be grounded in the problem which the

artefact was designed to solve – explaining why a particular approach to build the artefact

solved the problem more effectively than another approach. Ball (2001) cautions that

contributions which are based solely on the technology of the artefact are as perishable as the

technology itself. The artefact should outlast the study so it can be adopted, adapted and used

by others (Kelly 2004) – but ‘the theory must do real work’ (Cobb et al. 2003).

The Evaluation of DR centres around two sets of criteria, internal and external, shown in Table

4-3, as adapted from Rossi and Sein (2003). The description of the artefact – in terms of

organisation and function, as the interface between inner and outer environments – is a major

objective of design activity (Simon 1996, p. 9). The outer environment determines the

conditions for goal accomplishment; and if the inner system is properly designed, it will adapt

to the outer environment so that its behaviour will be determined in a large part by the

Figure 4-2: Design Research outputs (Purao 2002)

Artefact as Situated Implementation

Knowledge as Operational Principles

Emergent Theory about supporting a phenomenon

Information Retrieval Agent

How to generate access plans

to retrieve from heterogeneous databases

How to support retrieval from

multiple databases

Information model

Document technology (XForms)

The digital document

How to support medicationmanagement with a (digital) document

Example from Krishnan In current research

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behaviour of the latter (Simon 1996, p. 11).

The process of design is complex however, and its open-endedness and reliance on creativity

has made it a challenge for researchers to characterise and explain (Edelson 2002).

Additionally, a key feature of DR – that new insights can be pursued as they emerge leading

to changes in the intervention – signals caution, as it is possible to lose sight of the initial

purpose and reconsider this purpose, or perhaps fail to align action with redefined goals

(O'Donnell 2004).

An important point made by Hoadley (2004) is the usability of design vs. the context of use.

Hoadley stated that (in his study) there was a naïve assumption that usability would be the

primary indicator of successful design. However, usability does not always lead to use. There

were important interactions in Hoadley’s study between the research tools and the culture (of

the classroom) that evolved as tools influenced use; and use influenced culture and activity

structures – therefore the intervention really consisted of the tool plus activities as an

intervention, rather than ’tools-as-intervention’ (Hoadley 2004).

4.8 Aligning the research plan and design research processThis section describes the iterative approach of the research according to the DR principles.

Chapter 3 has already described the different scenarios which were included in the research

plan. The research plan is now aligned with the DR cycle, as are the outputs from these

scenarios and the literature review. Using the framework of the DR cycle according to

Vaishnavi and Kuechler (2005), the research cycles and outputs of the research project are

shown diagrammatically in Figure 4-3.

In keeping with the responsiveness of DR to contextual elements in the environment

(O'Donnell 2004), the different elements of research changed in keeping with the context in

question. From the literature review to the field study, the various outputs changed from

theoretical perspectives to ones which were more concrete.

Table 4-3: Design research criteria (Rossi & Sein 2003)

Internal criteria External criteriaMatch between the artefact and the abstract idea.(How well does the artefact embody the abstract idea that is being researched?).

Advancement of design theory.(Is the abstracted idea generalisable to other contexts or will at least advance understanding of other design contexts?).

Match with generally accepted principles of designed artefacts.

Are the ideas, if not the elements of the artefact, reusable?

Is the artefact a ‘good system’ as defined by the field (good interfaces, easy to use etc.?).

Advancement of information systems discipline.(Does the artefact behave in / influences/improves the environment / context in which it is intended to be used?).

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For example, the proposal moved from developing decision support for pharmacists and the

consideration of digital documents in the literature review, through proposals to develop an

information model, to a generic tool to support decision-making and proposed intervention to

improve practice. Tentative design moved from consideration of data collection tools and

XForms technology to an ‘essential’ information model, hospital model and community model.

The instantiated artefact began with a hospital-derived information model, the next cycle

improved on that model by testing the hospital model and adding elements for community

context; and the field study tested the community-based model. Performance measures in

the bench-testing scenario tested the hospital model for completeness and refined it for the

community setting, while the field setting tested the community model for effectiveness in the

intervention. Finally, the results measured the intervention. Emergent features in the various

settings guided the direction of the research (The Design-Based Research Collective 2003).

To echo a previous concern, all features of all contexts could not receive attention; and so the

researcher was required to make decisions about what were considered important aspects for

investigation – with the consequent risk that other important aspects may have been

overlooked (O'Donnell 2004). However, the goal of this project was not to ‘sterilise’ the

Figure 4-3: Project iterative research cycle and outputs

ResultsDid the model & document contribute to quality, efficiency or safety of the medication management process

Performance measures (evaluation)Field testing in ‘real’ scenario

Performance measures (evaluation)Feed back from prototype testing

ArtefactCommunity-centric information modelEnhanced digital document prototype

ArtefactHospital-centric information modelDigital document prototype

ArtefactHospital-centric information modelDigital document prototype

Tentative designModel for community and hospital information

Tentative designHospital information model

Tentative design‘Essential information’ model

Tentative designXForms technologyTools for data collection

ProposalEvaluate intervention in medication review scenario

ProposalDevelop generic tool to support medication-related decision-making

ProposalDevelop knowledge of information use by pharmacists & doctors, decision-making, work flow

ProposalDevelop decision support (pharmacists)Use for digital documents

Literature review Part 1 – The Hospital Scenario2A – Investigation of the



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naturalistic contexts from all confounding variables, but to develop flexible and adaptive

theories which would remain useful even when applied to new local contexts – to strike a

balance between refinement and adaptability (Barab & Squire 2004).

A setting like this provides concerns about rigour and relevance, as interventions cannot be

entirely controlled and interactions cannot known in advance (thus the implications for other

contexts and ’successful intervention’ elsewhere) (Hoadley 2004). These concerns were

addressed by:

• the appropriate application of empirical techniques (rigour) (Hevner et al. 2004)

• the investigation of an existing problem (relevance, i.e. lack of medication management

support); and

• contribution of interesting new knowledge to a community (Vaishnavi & Kuechler 2005),

which was the community concerned with medication management.

Critical to this approach was the researcher’s need to monitor his own agenda and influence

over results; and not only document the perspective or starting point, but also any relevant

interventional strategies used by him or the participants (Hoadley 2004).

In search of answers, DR requires more than simply showing that a particular design works –

it demands that the researcher generate evidence-based claims to address theoretical issues

and further the theoretical knowledge of the field (Barab & Squire 2004). In real-world

complexity, however, ‘best answers’ are often unknowable and the ‘good enough answers’

must suffice (Simon 1996. p. 28-29). Simon (1996, p. 28-29) calls this ‘satisficing theory’,

where a person accepts a 'good enough' alternative, not because this is preferred, but because

there is no choice. Although human choices are not consistent and transitive, we need some

criteria of satisfaction (Simon 1996, p. 29). This was the approach taken by means of the

different contexts in which empirical data was gathered.

As discussed in Chapter 1, the ability to provide comprehensive decision support in a variety

of contexts is difficult, if not impossible. Thus, the approach to design of the artefacts taken by

the researcher had ‘satisfaction’ in mind where these artefacts would provide a pragmatic and

‘good enough’ basis of support (with the health professionals’ knowledge) to ensure good

medication management. This approach was also in keeping with the notion that complexity

(of a structure) depends on the way it is described; and as most of the complex structures

found in the world are enormously redundant, this can be used to simplify their description

(Simon 1996, p. 215) – this simplification involved finding the right representation – which was

the goal of this research project.

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4.9 Chapter summaryIn summary, the DR method appeared to be the most suitable approach to underpin this

research project. This was not only based on the fact that it was an artefact-based intervention,

but also that the health domain is characterised by a complex and dynamic environment where

solving problems requires careful consideration of the mutual interaction between the

technology and the human user.

The use of DR in similar (although possibly less information intense and emotional)

environments of education and IS also support this choice. Importantly, the pragmatic,

‘satisficing’ approach of DR was a realistic stance for the outcomes of this project.

This thesis now turns to the unfolding story of the DR journey iterating through the different

scenarios, beginning first with the hospital use case, presented in Chapter 5.

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Chapter 5

Formulating the information model: the hospitalscenario

5.1 IntroductionChapter 4 reviewed and discussed Design Research (DR) and concluded that this method

was the most suitable approach for the present research project, for several reasons:

• the health domain is characterised by a complex and dynamic environment, where

solving problems requires careful consideration of the mutual interaction between the

technology and the human user

• the project was an artefact-based intervention

• a number of iterations would be needed before the ideal medication management model

could be developed; and

• the project clearly required the development of a software solution – making this an

almost archetypal design research project.

This pragmatic, ‘satisficing’ approach of DR thus seemed ideal for this project.

The project iterates through three investigation scenarios: the hospital requirements analysis

setting, the benchtop testing of the prototype; and the field studies in which the developed

prototype was tested. This chapter describes the hospital scenario, in which the preliminary

data on which the initial model was based were collected. The empirical research undertaken

in this phase provided answers to the first two research questions:

A: Can medication management-related issues in the hospital environment be addressed by the use of technology?

Answering question A involved investigating the hospital context to provide an initial

understanding of both medication-related information components, including workflow and the

decision-process for pharmacists, as well as medical officer (MO)1 activities, including

1. Medical officer (MO) will be used as a generic term for hospital doctors, including resident medical offic-ers, registrars and consultants.

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processes for ordering medication and perceptions of requests for information. Data collection

was focused on revealing the medication management processes and activities within the

hospital context, but some questionnaire components were designed to identify broader

information, so as to obtain a richer background and help in identifying major themes and

issues. These became the basis for developing the initial medication management model. A

full analysis of this material can be found in Appendix J.

B: What technology approach might be appropriate to do this?

Question B was addressed by means of an XForms implementation of the information model.

The development process is too detailed to describe in full in this chapter, so the discussion

will concentrate on illustrating the major aspects of implementation; and will provide selected

examples of digital document views. The full implementation details, programming source files

and file structures are contained in a series of appendices, summarised in Table 5-1.


• the ways in which the data were gathered is reported in Section 5.2

• a structured analysis of the data is presented under the 'themes' which emerged from the

analysis process, together with an analysis of relevant documents in Section 5.3

• Section 5.4 describes the formulation of the resulting information model

• Section 5.5 reports the subsequent development of the digital document prototype; and


Authors not previously introduced in this thesis may be cited or quoted in this and subsequent

chapters. This new material appears only where it is necessary to support assertions or to

explain concepts.

5.2 The Data Gathering Process

5. 2.1 Questionnaires and interviewsThe recruitment process began with an approach to the Directors of Pharmacy Departments

of the candidate adult hospitals within the Adelaide metropolitan area, using a mixture of email

Table 5-1: Technical appendices

Appendix Content

K Full technical and development details.

L Visual Basic (VB) browser code.

M XForms document code.

N Patient XML file structure.

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and telephone. These people became the pathways to the pharmacists and Medical Directors

who, in turn, suggested a number of candidate Medical Officers (MOs) who were approached

directly by telephone.

Once individuals had agreed to participate, they were sent the questionnaire by email, allowing

them some time to consider the questions. They were contacted one to two weeks later to

make an appointment for an interview. A few participants completed the questionnaire quickly

and sent it back to the researcher within that time but for the majority, the follow-up call served

as a reminder to complete the questionnaire. The interview used the questionnaire as a

foundation and was conducted at a location which was convenient for the participant – usually

their workplace. For pharmacists, the researcher attempted to organise the interview for the

same day as a work practice observation, but this was unsuccessful as most pharmacists were

too busy to commit to both activities within a single day. The time required for the audio-taped

interviews ranged from 30 minutes to 1.5 hours, although most were about one hour in length.

Overall, 20 participants agreed to be involved (11 pharmacists and nine MOs); and data

collection ran from the end of October 2004 to late January 2005. The breakdown of

participants' locations is shown in Table 5-2.

The specialities of the MOs included: general medical; aged care and geriatrics; respiratory;

endocrinology; obstetrics; cardiology; emergency and psychiatry. Resident Medical Officers

(RMOs) had an average of 4 years' experience; registrars had, on average, 8 years of

experience; and the consultant had 39 years of experience. The practice areas of the

pharmacists who participated in the study were similar to those of the MOs and included:

general medicine and aged care; psychiatry; respiratory; cardiovascular; community liaison;

gastrointestinal; rehabilitation; orthopaedic; emergency and intensive care. Years of practice

for pharmacists were in the range of 2-30 (average 15.7, median 13); and clinical experience

ranged from 1-27 years (average 9.5, median 6.5). All pharmacists, except the most

inexperienced individual, were undertaking, or possessed, post-graduate qualifications.

Table 5-2: The distribution of hospital participants

Hospital PharmacistsResident

medical officers (RMOs)

Registrars Consultants

A 2 3 1 0

B 4 1 2 1

C 2 0 0 0

D 3 1 0 0

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5. 2.2 Work practice observationsThe questionnaires and interviews provided data relating to the medication-related information

individuals said they used, as well as identifying both what information was missing and the

material respondents would like to have. Those responses enabled the development of a set

of expectations concerning which components should be contained in the model. The data

obtained from questionnaires and interviews were then triangulated by observing actual

practice on the wards. Identifying the information which was actually used in practice helped

to confirm or refute the need for the components identified as a result of the interviews.

Work practice observation was designed to study the day-to-day activities of clinical

pharmacists and their related information and knowledge use. These were arranged at times

convenient for the pharmacists to observe an ‘average day’ (to the extent possible). No special

meetings or activities were arranged. There were 12 work practice observations of 11

pharmacists (as one pharmacist offered a second opportunity to be observed in a different

clinical setting). Pharmacists were observed for a total time of 23.8 hours (average 2.0 hours

per pharmacist, range 1.0 to 3.5 hours). During observations, there were a total of 95 'patient

information encounters’1 (average 8.6 per pharmacist, range 3 to 12).

As a background to these observations, it is useful to describe the expectations of the

pharmacists in this role and what the process generally entails – these explanations are

provided in the next two sub-sections.

5. 2.2.1 Clinical pharmacy practiceStandards for the practice of clinical pharmacy in Australian hospitals are compiled by the

Society of Hospital Pharmacists of Australia (SHPA) Committee of Specialty Practice in

Clinical Pharmacy (SHPA Committee of Specialty Practice in Clinical Pharmacy 2005). The

ideal is to develop a Medication Action Plan for each patient, where the six fundamental

components of this plan are: interpretation of patient-specific data; identification of clinical

problems; establishment of therapeutic goals; evaluation of therapeutic options;

individualisation of therapy; and monitoring of patient outcomes. Although formal medication

plans were not seen during work practice observations, these components were certainly

fulfilled by the pharmacists under observation.

5. 2.2.2 The medication review process in the wardThe medication review process involved pharmacists assessing relatively standard

components of information (drug chart, patient case notes, laboratory reports); and applying

their knowledge to ascertain if there was an issue and/or if there were missing information

1. A ‘patient information encounter’ was defined as an encounter where the pharmacist was involved in reviewing, evaluating or discussing a patient using documented information or information sought from another health professional. Each patient was only counted once even if there was more than one case of information use or exchange for that patient.

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components impeding an informed review. Some pharmacists carried reference information,

such as drug information texts and treatment guidelines, while some carried their own patient

summaries. A simplified process for medication reviews is shown in Figure 5-1, although this

can be much more complex and may involve many iterations.

The pharmacist’s clinical role was overwhelmingly seen as promoting the Quality Use of

Medicines (QUM), followed by the provision of information and education to patients and other

health professionals. Drug safety was also mentioned specifically, however, this is also

considered a goal of QUM. This role was described as being supportive and practical, offering

advice rather than only information. This often involved problem-solving, requiring professional

judgement to balance the positive and negative consequences of a course of action in the

absence of a definitive answer. Views were also expressed that often a pharmacist’s focus

may only be on drugs, but it was more important to think more broadly about the patient.

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5. 2.3 DocumentsCollecting working documents was important to uncover all the possible information

components that might be used in practice. The researcher did this opportunistically during

work practice observations; as well as during some pharmacist interviews. A total of 53 sample

documents were collected from pharmacists. Duplicates were collected only where they

illustrated different use or issues. There were many similar documents, as hospitals used local

variations of the same types of form (e.g. medication administration charts). Examples of

documents included one or more of: prescription forms (outpatient and discharge); inpatient

prescription and administration forms; medication charts (standard and intermittent drug

Figure 5-1: Hospital medication review process

Ward

Pharmacist checks patient information

Issue?

Urgent?Community Pharmacy, GP

Missing info.?

Nurse, MO, Allied Health

Patient, family member

yes

no

no

yes

no

yes

Entryinto

notes

Nurse, MO

MO

Drug chart

Lab. results

Own notes?

Case notes (med., nurse, & other)

no

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administration); observation charts; patient summary lists; pharmacists' own notes; nurse

hand-over sheet; and laboratory reports. A complete list is shown in Appendix J. Only 52

documents were analysed as one document was an audit tool for clinical pharmacists and thus

was not considered relevant for this purpose.

5.3 Analysis and discussionThis section analyses and discusses data from the different sources: questionnaires and

interviews, work practice observations; and document analysis. In order to keep this

discussion to a manageable size, the questionnaires themselves and the detailed analysis of

the raw data are contained in the appendices. Table 5.3 summarises the location of this

information.

Many of the same questions were used with both pharmacists and MOs, to allow comparisons

of fundamental issues, e.g. goals for medication management and patient outcomes, with the

result that a considerable amount of rich data emerged. It was not possible to examine all this

material in detail, e.g. the reflection of pharmacists and MOs on goals for medication

management or patient care. However, these data contributed to the researcher’s broader

understanding of the issues that affected pharmacists and MOs. The questions posed to

pharmacists and MOs are shown in Table 5-4.

Table 5-3: Data-related appendices

Appendix Content

H Pharmacist questionnaires.

I MO questionnaires.

J Full analysis of hospital data.

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Table 5-4: Questions posed to pharmacists and MOs

Pharmacists MOsWhat do you think are the main aims of a pharmacists' clinical role?

What do you think are the main goals in medication management?

What do think are the main goals in medication management?

What do you think are the main goals for patient care?


Can you describe your relationships with other health professionals in achieving patient care goals?

What information components do you need to initiate a medication order?

What are the information sources you use in your work practice for patient medication management?

What information do you think pharmacists should have to allow them to contribute to effective medication management?

Have you ever needed to obtain information from sources other than in your practice environment?

Are you able to provide this type of information when you initiate the medication order? If not, what are the factors that prevent this?

Do you use any other (personal) knowledge in addition to information sources as part of your decision-making?

Are there any information components that are missing (if so, is this often?)

Are there ever any pieces of relevant information missing?

How do you manage with missing information components?

Do you think there are there any implications for medication management?

Do you think this has any implications for medication management?

Do you think there are there any implications for patient care or patient outcomes?

Do you think this has any implications for patient care or patient outcomes?

Are there any ways this information could be obtained / provided in your practice environment?

Are there any decision support tools in place to help with medication management?

Could a decision support tool help in supplying this information?

What is your understanding of the term 'decision support'?

How would you expect it to fit in to your work practice?

How would you expect this to fit into your work practice?

Is this realistic expectation in your current work scenario?

Is this a realistic expectation in your current work scenario?

What would expect from an 'ideal' decision support tool?

What features / support would you expect from an 'ideal' electronic decision support tool?

How generally acceptable do you think reminders / prompts are or would be from an electronic system (either decision support generally or from a prescribing system)

What factors would make alerts / prompts from an electronic system (more) acceptable?

Under what circumstances do you think it is acceptable to be asked to enter missing information required for a medication order, into an electronic system?

Would this be more acceptable if the request was accompanied by some justification?

Are there any occasions when you would accept such a system blocking the generation of a prescription or order?

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Grouping data and developing concepts was based on any relevant models from the literature

where possible, e.g. openEHR, CDA, Genres and PCNE – mentioned in Chapter 3. However,

as these models were not considered suitable for this project, concept development was based

on the researcher’s own domain experience and knowledge of the issues important for

medication management in the health sector. These were kept broad deliberately to allow

better awareness of the area rather than risk losing meaning through over-categorisation,

since the frequency and type of responses could potentially shed light on the relative

importance of particular concepts within and between groups.

A number of themes became apparent very early on during the data collection and analysis

process. Some of these themes were relevant to the project, directing the approach to the

information model, or suggesting factors which could impinge on the acceptability of using a

document approach for user-interaction. Other themes were of professional interest to the

researcher, such as the reporting of Complementary Medicines (CMs). Analysis and

discussion throughout this chapter (and, indeed, the next two chapters as well) is grouped

under these themes, so as to make the findings more readily comprehensible. This grouping

process combines data from questionnaires/interviews with findings from the work practice

observation, although the document analysis is discussed separately. The themes and their

respective sections are shown in Table 5.5.

5. 3.1 Missing information and surrogate valueThe many questions relating to this topic were based on the researcher's expectation that

missing information would be a significant problem for both pharmacists and MOs – this

expectation was quickly confirmed and, indeed, the issue of missing information also emerged

in the answers to other questions. This section brings together all the responses relating to

missing information, as well as techniques used by respondents to address or alleviate

information gaps.

Table 5-5: Research themes

Section Theme

5.3.1 Missing information and surrogate value.

5.3.2 Information granularity.

5.3.3 Conversation and communication.

5.3.4 Time constraints and summary information.

5.3.5 Decision support tools.

5.3.6 Systems for experts rather than expert systems.

5.3.7 Complementary and Over-the-Counter medication.

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5. 3.1.1 Missing Information relevant to Medical Officers

All MOs confirmed the widespread problem that a great deal of information of all types was

missing – '90% of the time'. This situation could lead to 'diagnosis by treatment', because when

important information was missing, they frequently did not know what condition they were

treating for a few days, during which time the diagnosis was guided by a 'suspicion' or by

identifying what treatment did or didn't work. Another clear message was that MOs often did

not know what information was missing: i.e. 'you don't know what you don't know'.

Knowledge concerning the patient's medications was considered important, especially those

medications which had been tried in the past, as this could avoid repeating past medications

or overlooking a useful medication. One MO stated that, on patient admission, information

which would influence prescribing was missing in about 50% of cases - patients frequently

could not identify what they were currently taking (e.g. a 'little pink tablet'). A similar problem

applied to MOs in outpatient areas.

The disparate nature of information was also a problem – what laboratory tests patients had,

what the GP had done, social contexts, multiple patient presentations to GPs or pharmacies –

compounded by the MOs' inability to deal with this disparity because of time constraints.

5. 3.1.2 Missing Information relevant to Pharmacists Pharmacists actually described two types of missing information: one related to clinical

practice; and the other related to the medications themselves. Pharmacists often found that a

range of information was missing, but their particular focus was on medications, both past and

current; and on information which revealed the patient context (such as why drugs were

prescribed or background detail relating to an Adverse Drug Reaction (ADR)). A further

problem was information quality, since information was frequently ambiguous or poorly

documented – or, by contrast, well documented but inaccurate. Overall, participants believed

that the amount of information missing or requiring clarification was increasing.

Pharmacists, too, frequently mentioned the disparate nature of the information they needed.

They also added that it may not be 'missing' per se but was rather inappropriately located, e.g.

allergies and alerts might not have been filed in the correct location in the case notes. It was

seen as a major role of the pharmacist to ensure that information was transferred or clarified,

e.g. the nature or severity of allergies or ADRs. Where pharmacists kept their own patient

notes, a potential issue arose if they had important information about the patient and did not

Medical officers often found themselves guessing

Sometimes ‘you only get a partial glimpse of the patient’

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record this somewhere appropriate in the case notes, so that another decision-maker could

obtain this information when facing the same problem at a later date.

5. 3.1.3 Pharmacist techniques for obtaining missing informationPharmacists relied on multiple information sources (GPs, community pharmacists, patient or

family members, GPs' letters, compliance aids, patients’ lists and actual medications); and

routes (communication by paging MOs in hospital, or phone or fax).

Generally, missing components were first sought from available paper or on-line sources; if

this was not successful, pharmacists would turn to conversation with others. The importance

or urgency of the information to patient management dictated whether obtaining missing

information required immediate communication. The source(s) of this information depended

on both the type of information (e.g. community pharmacies to identify previously prescribed

medications, or patients themselves to confirm aspects of current medication); as well as on

the pharmacist's previous experience. In the latter case, knowledge of the 'system' meant a

pharmacist had the best chance of finding the relevant information. Multiple information

sources could reveal problems (e.g. therapeutic duplication) but, paradoxically, could

themselves cause additional problems, as it was difficult to determine the real scenario when

equally 'reliable' sources of information were in conflict - a resolution would still be required,

despite this uncertainty.

Professional colleagues were an important source of information, as participants felt that their

feedback would be based on clinical experience and would thus be more relevant. Often, there

was information pharmacists would not find unless they asked the right person the right

question.

Information could generally be found if sufficient effort was directed towards searching through

the numerous sources and the volumes of patient notes – and missing laboratory test results

could be re-ordered although, in some cases, this required the MO to reassess the clinical

situation and perhaps re-prescribe medications. Time lags in obtaining missing information

could be quite lengthy – occasionally, anomalies or missing information were found after the

patient had been discharged, requiring follow-up in the community.

An interesting issue was the transfer of information between the hospital and the community.

There was an expectation that both groups would provide information to one another, although

‘any scrap of information’

Information transfer between the hospital and the community was a 'minefield'

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participants believed that neither the hospital nor the community really did provide as much

information as was possible, leading to great frustration on both sides.

5. 3.1.4 Medical Officers as a source of information for pharmacistsThe aim of investigating this issue was to determine how far the roles of pharmacists and MOs

overlapped, that is whether information that was missing 'downstream' for pharmacists could

or would be provided upstream (into a system) by the MOs. An MO would not normally directly

supply a pharmacist with all the information required for a medication review – only with that

related to a medication order. The pharmacist would seek supplementary information from

other sources. However, it was important in a general sense to ascertain potential information

gaps for the pharmacist.

From a general perspective, it eventuated that MOs thought pharmacists should have access

to the same information they had themselves, believing that pharmacists were entitled to this

as members of the professional team. In addition, MOs believed that a further major

consideration was patient safety – the more people who were involved in managing the

patient's medication, the better the chance of obtaining the right information and reducing

medication errors. Pharmacists' different background and perspective were highly regarded by

MOs, especially in the case of long and complex medication history and in the case of chronic

patients, whose conditions might have evolved over decades.

This support by MOs for pharmacists to have access to all information meant that an

information model could consider any relevant information component without potential conflict

caused by issues of 'ownership' or professional barriers (real or imagined). The sole issue

raised was that of patient privacy and even this provided no hurdle since all participants

believed it was crucial for health professionals to understand one another in the course of

information sharing.

Many participants were willing to accept a system requesting information entry by MOs, but

this appeared to be relevant only in a small number of cases, such as: weight and creatinine

values for patients relating to renally-cleared drugs (e.g. gentamicin or enoxaparin), or INR

values in warfarin dosing. Other than for warfarin, there were probably only a minority of

patients who actually required 'fine tuning' based on laboratory values. A suggestion by one

MO that an estimated weight value could be used when accurate information was not available

was rejected by others, on the grounds that the estimated value might remain in the system

and not be corrected, leading to potential errors at a later date. Another MO believed that data

entry would not happen at all.

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Essentially, all MOs stated that it was not possible to provide all the required information. The

major problem was that the inpatient medication chart (the primary method of communication

between doctor and pharmacist) did not cater for conveying any information other than

allergies. A proposed Australian national standard inpatient medication chart (being

formulated at the time of the project) was suggested as going some way to resolve this lack

(e.g. allowing the communication of some laboratory values), but still would not provide all the

necessary information.

The researcher found it difficult to assess whether the information MOs were unable to provide

was the same information which pharmacists found difficult to obtain. This discussion proved

to be an introduction to the problems of the unavailability of, and disparate nature of,

information required for patient medication; and the lack of time to address this lacuna.

Although this question was originally designed to identify information gaps for the pharmacist,

its answer also revealed information gaps for MOs – clearly, information gaps are a

widespread problem right across the hospital system. Overall, a request for some specific

items of information was considered to be acceptable, as long as it was important information

and the need to enter the data could be bypassed. The researcher formed the impression that

a request for information from a computerised system would not be taken as seriously as if the

same request came from a person.

5. 3.1.5 Alternative information sources for MOsFurther information required by MOs was most often sought from General Practitioners (GPs),

although this was a time-intensive process. MOs did not often think of communicating with

community pharmacists and, where they did so, usually delegated this to more junior medical

staff or to hospital pharmacists. Communicating with GPs (i.e. other doctors) was part of the

medical culture and MOs were less aware of the role of community pharmacists.

The combination of much of medicine being 'guess work' with an abundance of information

sources was the source of much difficulty in obtaining accurate and timely information. Further,

not all information was useful, e.g. where a patient had numerous laboratory tests during a

single admission. However, there was a balance between too many tests (often requested by

younger and less experienced doctors) against the risk of errors of omission when doctors did

not order tests because they were confident of the likely results. This problem of the need to

obtain the 'right' information was further complicated by testing essentially for medico-legal

reasons (i.e. tests undertaken to protect the hospital against potential legal action at a later

date) which again could provide information unnecessary from the point of view of a patient's

medication management.

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5. 3.1.6 Work practice confirmation

The work practice observations confirmed the extent of missing information, which is

summarised in Table 5-6. As had been mentioned in interviews, missing information about

medication was the most significant problem, followed by information related to allergies.

Overall, almost three items of missing information were experienced each hour, or six per

pharmacist. On average, there were two items of information missing for every three patients.

These were all items of information deemed necessary for decision-making for that patient and

important enough to be pursued by the pharmacist. Conversely, where the missing information

was not sufficiently important, the pharmacist did not pursue it.

The need to pursue a piece of missing information could be seen as a surrogate for the value

of that component to the decision-making process and, consequently, became an interesting

hypothesis for the researcher and was a signal for the inclusion of that component into the

information model.

Missing information observed in work practice is also compared to that mentioned by

respondents during interviews in Table 5-7. It is clear from this table that pharmacists' and

MOs' views on what information was missing and how frequently they missed it did not relate

very accurately to the situation in practice. Missing patient information (notes) was not

specifically mentioned by either pharmacists or MOs, but was common in practice. However,

MOs did mention items such as treatment history, which are an information subset of patient

notes (the superset).

Table 5-6: Missing information experienced by pharmacists

Category pharmacist observation

percentage of total per hour per

pharmacist per patient

Current medication 26 42% 1.1 2.4 0.27

Allergies / sensitivities 10 16% 0.4 0.9 0.11

Specific patient information / social

7 11% 0.3 0.6 0.07

Patient notes 6 10% 0.3 0.5 0.06

Medication history 5 8% 0.2 0.5 0.05

Treatment history 5 8% 0.2 0.5 0.02

Laboratory tests 2 3% 0.1 0.2 0.02

Community pharmacy 1 2% 0.0 0.1 0.01

Total 62 100% 2.7 5.6 0.65

The value of information is based on its context of use

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An interesting observation was that allergies and sensitivities not mentioned by MOs as

missing information – although their importance was noted by this group of respondents – were

a real problem for pharmacists. This may be as simple as information being available to MOs

but not being transcribed to medication charts when prescribing occurs. Some items which

were described as missing during interviews were not recorded as missing during observation,

but this could be due to the length of the observation period – a longer period of observation

might provide a more accurate picture.

Additionally, for pharmacists, interpreting changing drug information was also an issue; and

constant revisions were needed to ensure up-to-date drug information – these were areas of

MOs' questions. Coping with missing drug information meant reassessing older information,

extrapolating from studies or, in some cases, using previous clinical experience. Where there

was limited evidence for uses of new drugs, no clinical trials or poor clinical trial design, it was

difficult to evaluate new therapy against existing therapy. Here the pharmacist would use

knowledge and experience to hypothesise answers.

5. 3.1.7 The implications of missing informationAlthough missing information was common, the more important question that arises is how

important is this. When asked, MOs and pharmacists both believed that missing information

had significant implications, particularly in terms of adverse effects and patient safety.

Table 5-7: Missing information – interviews and observed

Category MO interview pharmacist interview

pharmacist observation

Active problems 1

Adverse drugs events 3

All information 1 3

Allergies / sensitivities 1 4 10

Community pharmacy 1 1

Co-morbidities 1 1

Creatinine 1

Current medication 6 5 26

Drug supply 1

GP notes 1 1

Laboratory tests 3 2

Medication aids 1

Medication history 4 4 5

Patient notes 1 6

Specific patient information / social 1 7

Treatment history 4 5

Treatment indications 1 3

Weight 1 2

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In terms of medication management, MOs were primarily concerned about being unable to

carry out a proper patient assessment. They identified potential problems with retrying

previously unsuccessful medications, or overlooking medications that could be useful. These

were potentially important issues for 'sicker' patients who required immediate treatment. In

some cases, a patient could even be discharged with a condition that still required treatment;

and MOs were not confident that the GP would follow up on problems.

Similarly, pharmacists were concerned that an uninformed review of a patient might impair

good decision-making and appropriate drug use, risking duplication of existing medication; or

unnecessary, poor or unsafe use of drugs. They saw the 'best guess' approach, which

inevitably resulted from missing medication-related information, as being highly undesirable

because they were unable to offer sound advice under these circumstances.

As with medication management, all MOs stated that missing information had implications for

patient care. Their main concerns were poor patient outcomes – in particular, medication

errors leading to adverse effects, unplanned readmissions or, occasionally, poor or delayed

(disease) symptom control. Typical examples of potentially serious adverse events resulting

from missing information included: prescribing beta-blockers for cardiac patients having

underlying asthma or reversible broncho-spasm (a drug type contraindicated for this group);

prescribing drugs to patients allergic to them (e.g. penicillin, allopurinol); and drug class

duplications. The side effects of drugs it was not known a patient was taking could also be

misinterpreted as disease symptoms, leading to incorrect diagnoses or inappropriate

treatment.

Fortunately, even though missing information which could potentially lead to adverse

outcomes was common, ADRs were not – although the relationship between missing

information and poor outcomes was difficult to quantify. The issue was more likely to concern

quality of life than adverse outcomes per se. Despite the many factors that could contribute to

avoidable errors in hospital, MOs still felt that the chance of detecting medication-related

problems was greater in hospitals than in the community. The presence of trained

MOs were concerned about ‘being in the dark’ when beginning therapy

It was frustrating for pharmacists to be forced into making decisions which could inadvertently lead to errors

All MOs had seen adverse outcomes resulting from missing information

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professionals – doctors, pharmacists and nurses – within the hospital environment meant that

adverse reactions or events could be identified and treated quickly.

Pharmacists were primarily concerned about patients’ understanding of their medications and

compliance. Although ADRs were a concern of pharmacists, and were stated to be a common

occurrence, they were not often seen first-hand. This finding was in stark contrast to the

responses from the MOs, who believed ADRs were uncommon. Whether this contradiction

indicates a lack of awareness on the part of the MOs, or whether MOs were only concerned

with major adverse drug events, it is clear that there was a significant (and potentially very

important) difference in the views taken by MOs and pharmacists to the potentially adverse

outcomes of inadequate medication-related information in a hospital setting. Nursing staff

were of great value in terms of identifying the true state of affairs here: minor ADRs might well

not be documented, but nursing staff would be aware of them because of their more immediate

relationship with the patient.

Examples of serious ADRs volunteered by pharmacists included: patients receiving drugs to

which they were allergic; a patient with a bleeding ulcer given warfarin (and consequently

requiring intensive care); and a case of unintended bleeding when the dose of the

anticoagulant clexane was not reduced for a patient in renal failure. The impact could also be

secondary, e.g. an ADR might in itself be minor, such as increased ataxia, but this could result

in more frequent falls – potentially far more serious (as falls in the elderly are associated with

an increase in mortality (Donald & Bulpitt 1999)).

In summary, the widespread problem of missing information evident in the literature was

confirmed very early in this scenario. Any type of information could be missing, but the most

frequent – and of most relevance to this project – was medication, both current and historical.

Missing information clearly has a profound effect on the effectiveness of decision support

systems as they cannot function in the absence of relevant information e.g. calculation of dose

in the absence of patient weight, or prescribing recommendations in the absence of a coded

patient diagnosis.

A way forward may be to allow a decision support system to operate with missing information,

but to signal caution or limit recommendations; and to highlight the need for clinical judgement.

This approach would also minimise the impact on work process.

In terms of this project, a major outcome of the hospital scenario was that missing information

Not only could missing information lead to an ADR, but also lead to the inability to detect one

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became important as a basis for model development – its inclusion in the model was based on

the surrogate value of whether pharmacists pursued it for their decision-making.

5. 3.2 Information granularityOne important aspect of information (whether for use, requirements or because it was missing)

was granularity. This could range from patient case notes to specific data items such as a

laboratory value and was very much driven by the intent of the health professional.

5. 3.2.1 Information required by medical officers to initiate a medication orderMO’s information needs when initiating a medication order could be summarised as: what is

wrong (with the patients); what medications are they taking; and are they allergic to anything?

A particular aim was to streamline medications for the patient – polypharmacy, and its potential

to affect patients' ability to cope after hospital discharge was seen as very important. One MO

was concerned that once patients were discharged there was a danger GPs might simply (re-

)write repeat prescriptions for the medication(s) and that patients would then remain (possibly

wrongly) on those medications without further review.

5. 3.2.2 Information used by pharmacistsInitially, pharmacists were asked what types of medication-related and non medication-related

information they required. However, it became apparent to the researcher that all information

related either directly or indirectly to medication. For example, personal history might relate to

patients' ability to manage their medication at home.

The principal sources of patient-related information were the patient case notes and inpatient

medication chart. The sources could vary greatly in form and content; and information could

be obtained in person, by phone, formally or informally, internally or externally to the hospital,

from electronic or paper copy sources; or from other health professionals, laboratories,

patients or care givers. The availability of reference information was considered a lesser

problem than obtaining patient-related information.

The use of summaries proved very important. Some pharmacists kept their own patient

summaries of what was considered the most important information, although these were

difficult to maintain with large numbers of patients. Summary sources produced by other health

professionals were also considered useful, e.g. a nursing hand-over sheet was a simple and

efficient way to transfer basic information (e.g. diagnosis) between nursing shifts. On the other

hand, medication histories by MOs were not always trusted, as pharmacists considered

doctors were not sufficiently thorough in assessing sources. Notes from other pharmacists

Pharmacists sought information from ‘anywhere you can get it’ or from ‘anyone with anything to say’

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were more highly valued, as they had been developed by professionals with the same

perspective. Nonetheless, participants noted that such information could be out-of-date and

transcription errors were a common problem.

Patients themselves were considered a useful source of information, although not always

reliable, e.g. psychiatric patients or elderly patients with cognitive impairment such as

dementia were clearly unreliable sources. Sometimes patients were unsure of what they were

taking, or had not been fully informed by the doctor. Patients were thus most frequently used

for clarification of medication issues, rather than to compile an accurate history.

5. 3.2.3 Observed information use by pharmacistsThe information sources actually used by pharmacists during work practice observations are

summarised in Table 5-8. These were categorised by the researcher under the headings of:

conversation, on-line and paper sources, in line with Paepcke (1996), since Paepcke's intent

was to investigate the sharing of information by loosely coupled work groups needing to

structure information for flexible use – a use very similar to this project. The manner in which

information was obtained had implications for how it could be accommodated (or not) within

the information model.

The majority of information was obtained from paper or on-line media, with the bulk (not

surprisingly) coming from medication charts and patient case notes. Reference sources,

although mentioned by pharmacists as general requirements were seldom used in practice. A

vital amount of information gathering, however, took place during conversation, highlighting

information shortfalls in other sources. In some cases, conversation was the first route used –

especially where there was a need for a quick summary of 'where the patient was'. This could

save considerable time for the pharmacist in catching up with the patient's current situation,

especially where there had been a great deal of activity around the patient, or where the

pharmacist had not reviewed the patient for some time. This important issue is discussed

further in Subsection 5.3.3.

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In summary, the nature of information ranged from patient case notes to specific data items

such as a laboratory value, i.e. from aggregate to singular information sources. This was very

much driven by the health professional's particular need – did they know little about the current

situation, requiring more aggregate information such as the case notes, or did they just need

a data item on which to base a particular decision? In some cases, information was first sought

through conversation with others. This has significant implications for the representation of

information in clinical systems. Participants also mentioned they wanted 'everything', but a

more useful day-to-day source would take the form of a concise summary of important issues

for the patient. There is enormous difficulty in providing all patient data at an atomic level

suitable for patient-centric decision support – this is affirmed by the vast efforts in producing

taxonomies and terminologies on which to base decision support systems. In contrast, clinical

narrative (free text), although useful for communication, does not readily underpin decision

support (e.g. alerts and reminders).

The researcher believes that this contradiction represents a tension for the design of health

information systems – the need for atomic data to develop shared terminologies and

ontologies on which to base decision support systems and allow epidemiological research,

against the need to efficiently communicate and share contextual information for patient care.

Table 5-8: Information sources used by pharmacists

Sources Information encounters (%) Encounters

per hour

Encounters per

pharmacist

Encounters per patient

Conversation 91 28.4% 4.0 8.3 1.0Patients 20 6.3% 0.9 1.8 0.2

Nursing Staff 29 9.1% 1.3 2.6 0.3

Medical Officers 34 10.6% 1.5 3.1 0.4

Other 8 2.5% 0.4 0.7 0.1

On-line 20 6.3% 0.9 1.8 0.2Laboratory systems 14 4.4% 0.6 1.3 0.1

Other 6 1.9% 0.3 0.5 0.1

Paper 209 65.3% 9.2 19.0 2.2Medication 72 22.5% 3.2 6.5 0.8

Patient case notes 51 15.9% 2.2 4.6 0.5

Own documentation 40 12.5% 1.8 3.6 0.4

Patient medication or aids 9 2.8% 0.4 0.8 0.1

Other 37 11.6% 1.6 3.4 0.4

Total 320 100.0% 14.0 29.1 3.4

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From this researcher's perspective, as information needs were reported at different levels of

granularity, it became apparent that the information model, and subsequent decision support

tool, should also reflect this variety of levels of granularity.

5. 3.3 Conversation and communicationThe questions about seeking missing information made it clear that pharmacists

communicated with other health professionals frequently and often opportunistically e.g.

during ward rounds and at ward meetings. Communication tended to be of three main types:

seeking patient-related information; offering medication-related information (in patient

contexts); and providing more general drug information or education.

5. 3.3.1 Pharmacist communication with Medical OfficersCommunication with MOs' was routine and open. With the more junior MOs, this was more

informal; and tended to concern day-to-day management or clarification of drug therapy.

Communication with medical consultants was more infrequent and often more formal and

consultative, i.e. requiring more specialist knowledge, or further investigation of additional drug

information resources.

Importantly, some of the information gained from MOs was background patient information to

which pharmacists would not otherwise be privy. Scattered information meant that

communication with the MO was a much easier path for the pharmacist to obtain relevant and

important information about the patient. Moreover, as doctors often made the final decisions

about patient treatment, pharmacists believed it was important to communicate with them

directly.

5. 3.3.2 Communication with nursing professionalsCommunication with nurses also occurred frequently and opportunistically. Nurses usually

requested practical information about the administration of medications, dosages and safety,

while pharmacists sought day-to-day management and practical information from nurses

about patients.

Nurses were able to provide a quick picture of the patient and nursing notes were often

considered a better source of information than medical notes. Nurses could also be a better

source of patient-related information than the patients themselves could, as patients might be

Pharmacists believed they gained significant benefit in terms of communication by ‘being on the wards’

Nurses were the best source of observed patient information

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too subjective or unreliable. Nurses were also valuable in providing feedback about patient

response to changes in medication (e.g. the level of drowsiness); and could act as sentinels

for drug-related problems making the job a lot easier.

5. 3.3.3 Other pharmacistsCommunication between hospital pharmacists generally occurred where one was a specialist

in an area of practice, had greater experience, or possessed local knowledge. These were also

opportunities to obtain other pharmacists' opinions and obtain confirmation of initial thoughts.

Sometimes this allowed less experienced pharmacists to 'get a feel for ' a decision process

used by more experienced pharmacists. It could be difficult for younger pharmacists to deal

with questions where there was uncertainty and where no structure (other than experience)

existed to teach these skills. Not all communication, however, related to clinical issues, some

dealt with the practicalities of service delivery, e.g. service rosters. Communication with the

dispensary staff was also important, as this could lead to the detection of important or unusual

changes that had occurred in the ward. Pharmacists in the community were an important

source for information related to medications dispensed or supplied to patients in the

community, such as Over-the-Counter (OTC) medication.

5. 3.3.4 Other health professionalsInformation sought by other (Allied Health) professionals was invariably related to the

administration of medication, such as how and when to give medication. Information sought

from this group of professionals was largely concerned with patient issues affecting

compliance. For example, Speech Pathologists could advise on anatomical issues that

affected oral administration; and Social Workers could indicate whether social issues could

affect compliance.

5. 3.3.5 Pharmacist conversations observed during work practiceWork practice observations confirmed the importance of conversations as a method of

information transfer; and these were analysed on the basis of who was involved in the

conversation (Table 5-9). This table shows the number of conversations originated by the

pharmacist (From); and those originating from others.

A team approach and multi-disciplinary care was considered important by pharmacists

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.

The total number of conversations which took place between pharmacists and all other groups

during the 23.8 hours of observation was 152 (6.4 per hour), an average of almost 13 times for

the typical observation period. Eighty-nine conversations originated from pharmacists and 63

from other people. Pharmacists asked more questions of nurses, than nurses asked of

pharmacists, suggesting that pharmacists saw nurses as an important source of information.

During conversations, pharmacists often took the opportunity to provide more background

information or education, e.g. pharmacology, drug usage, formulations or availability; or drug

policy. This happened on 17 occasions with nurses and 21 occasions with MOs.

There were also a number of other interruptions not related to the specific role of pharmacists

that occurred on 16 occasions, including: answering the phone, or handling general ward

enquiries from patients, family or others etc.

A very important feature of conversation was that the information exchanged related

specifically to the patient and the immediate problem – there was no unnecessary information

to process and, consequently, this was very efficient. One weakness of exchanging

information in this way, however, is that it leaves no record of the information exchanged.

Other pharmacists or, indeed, MOs needing to take up the care of this particular patient at a

later time would therefore have no idea of the additional information sought or obtained.

The significant use of conversation by health professionals as means of information gathering

in the hospital environment suggests that it would be difficult for them to gather all the

information they require for decision-making without conversation. Further, there is some

information – the tacit knowledge of other health professionals – that is not available to

pharmacists other than by conversation. The implications for designing decision support

systems is that the information models that underpin them will be incomplete – missing will be

Table 5-9: Conversations between pharmacists and other professionals

Medical officers Nurses

Other pharmacist

sLaboratory Other Total

From pharmacist to..

35 42 8 1 3 89

From others (to pharmacist)

30 29 4 0 0 63

65 71 12 1 3 152

Conversation played an important role for pharmacists, for quick, contextual summary information about patients, relevant to their needs

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the information that health professionals exchange by conversation.

In addition, as health professionals have a strong desire to be able to communicate and share

information (including their peers in the wider community), the decision support solution needs

to be one which supports or, at least, does not hinder this desire.

5. 3.4 Time constraints and summary informationAnecdotally, lack of time is a considerable issue for health professionals when attending to

patients. This research project confirmed that the time to find, assimilate and interpret

information in the inpatient setting was a significant issue for pharmacists; and still more so for

MOs. This problem also affected MOs in outpatient areas, where lack of time to deal

adequately with patient problems was compounded by a lack of information on the part of

patients themselves concerning their medication.

Time also had an impact on where information was sought by pharmacists – depending on

how quickly the patient was moving through the system; and what or who was available as an

information source. This was also helps to explain why conversation played such an important

role for pharmacists. In addition, time was cited as a problem in using reference resources as

'one won't know the answer to a question simply because there is no time to look'.

Despite the need to have all information available for a particular clinical decision, the

possibility of presenting an artefact with summarised, relevant patient-related information was

seen as useful. A single page was suggested as a target length – if the summary was too long,

it would not be used. Bringing simplicity to actions was considered a worthwhile plan, e.g.

through a simple aggregation of 'one-line' problems and actions; and the use of flags.

One pharmacist engaged in medication reviews outside the hospital suggested a minimum

data set could provide a portable information representation suitable for a range of users.

However, as pharmacists in hospitals were used to accessing 'everything', this was seen as a

problem for a Decision Support System (DSS). Participants acknowledged that it would be

difficult to achieve a trade-off between displaying essential and all information. As further

evidence of the value of summary information, some pharmacists kept their own patient-

related summaries

The need to cope with many patients and press on with ward rounds is a major deterrent to interaction with decision support systems

The fact that medical staff did not have the time to focus on medications-related issues in sufficient detail, confirmed the important role of pharmacist interventions in preventing ADRs

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In summary, time was mentioned as being a significant issue to find and assess information;

and of relevance to this project, the ability to interact with a decision support tool. However, the

concept of a relevant information summary as the interface to a decision support tool was

considered a possible approach to address time constraints. The next section of this chapter

therefore discusses decision support tools – and the experience which participants have had

with such tools – in some detail.

5. 3.5 Decision support toolsAt the beginning of the interview, participants were asked about their experience with

electronic decision support tools, as prior experience could influence opinion and expectations

of such tools. Both groups had exposure to decision support tools, although many of these

were simple information retrieval or laboratory reporting systems existing at the hospitals –

reflecting the day-to-day activities. In addition to having more experience or exposure in this

area, pharmacists offered more opinions, particularly relating to the lack of success or

usefulness of the systems they had encountered – hampered by poor training or

understanding of how the systems functioned.

5. 3.5.1 Decision support tools used by pharmacistsPharmacists were asked explicitly about decision support tools which supported general or

clinical pharmacy practice, although there was generally no major distinction made between

these.

One hospital dispensing system in use did provide decision support features such as: drug-

drug interaction checking, checks for therapeutic duplication; and dose-checking. However,

drug information generally supporting the dispensing systems was rarely evidence-based and

not user-friendly - a 'best guess' was often still required. Other decision support tools were

unsophisticated, being largely passive information sources or on-line calculators. Pharmacists

also included paper-based information sources and guidelines, a drug information service; and

computer-based tools for personal use (spreadsheets). Much discussion concerning clinical

systems centred on OACIS (a South Australian repository of clinical information that includes

laboratory and radiological results). This had some ability to generate electronic discharge

summaries, although it was noted that the information in this system was not always correct.

The value of colleagues was again raised as an important resource, particularly in the

specialist area of drug information. One pharmacist highlighted texts as better, more portable

and more concise information compared to ward-based, on-line sources - a challenge for

developing useful tools.

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5. 3.5.2 Pharmacists' understanding of decision supportThere was a wide range of interpretations of decision support, with many views about

information integration, prompts and alerts; and mentions of evidence-based information. To

help with the analysis of decision support concepts mentioned by participants, the researcher

organised these into categories – supportive, prescriptive, explanatory, outcome; and ‘other’,

as this helped to explain the level of sophistication of the concepts. The concepts were also

graded according to the NEDST types previously described in Chapter 2 – this complete

analysis is shown in Appendix J.

One pharmacist saw decision support as: 'information used in conjunction with what you

already know (professional knowledge), and what you know about the patient, to make further

decisions about management' – undeniably, a tool to complement the use of personal

knowledge. However, most of the interpretations described the simplest NEDST types. Some

participants made no distinctions between computer, telephone or paper-based decision

support. The researcher believes that many pharmacists based their perception of what

decision support was on their personal experiences of simple hospital systems. It is hardly

surprising, then, that when clinicians (in the broadest meaning) are asked what they want in a

decision support system, they find it difficult to express their requirements succinctly and

clearly. Consequently, attempts to consolidate requirements are difficult and there is little

success in terms of workable systems. Further, there is a clear opportunity in these hospitals

to develop more sophisticated decision support for both pharmacists and MOs.

5. 3.5.3 Decision support and Medical OfficersAlthough MOs believed that a decision support tool could help in providing information, the

brevity of their replies suggested there was little familiarity with the notion of decision support

– one MO even required clarification of the term. This is not surprising, as the researcher’s

experience in hospitals reveals there is a lot of discussion and belief about the positive value

of ‘decision support’, without much understanding of what this actually entails.

5. 3.5.4 Fitting decision support into work practiceTo allow comparison between MOs and pharmacists, the researcher categorised responses

from participants as systems requirements based on Pleeger (1998). These categories

included: physical environment, interfaces, users and human factors, functionality, data,

resources, security and quality assurance.

One interesting difference was that pharmacists tended to concentrate on how decision

support might be delivered (the physical environment), whereas MOs were more focused on

what would be delivered (the nature of the information). There were no answers about the

resources that might be required for implementation, although this could be because the

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phrasing of the question was not designed to elicit answers of this type. Security and Quality

Assurance of systems were also not mentioned, but this may be because of the hospital

environment – hospital staff are inclined to assume that attention to such issues will be taken

care of by hospital IT departments.

Most pharmacists suggested that existing hospital computer networks could be used to deliver

decision support, as there were few issues about accessibility. Some did mention that PDAs

would be useful for increased portability, although there was a concern about the bulkiness

and speed of these devices. The level of information available on PDAs, however, was

expected to be the same as for PCs! Accessibility and speed were mentioned as the critical

factors to use – without these, other means would be used to find information.

There were some concerns expressed about how a DSS should fit in the workplace. One

pharmacist considered that overly simplified therapy guidelines were inappropriate – a better

solution would be to provide reference information, educate and allow interpretation.

Another view was that the DSS should function even in the absence of information. Of course,

with some information, e.g. weight, this would limit the ability to calculate or check doses.

Participants believed that although the system should be aware of the absence of some

information, it would be unable to judge the importance of that piece of information. In these

cases it would be better to have no information (and deal with that) than be given a wrong

answer.

Some discussion also touched on the use of default system values. It was felt to be critical that

users of such a system be able to distinguish between e.g. the absence of an allergy (i.e. no

allergy) and the absence of an answer to the question of whether the patient had a drug allergy

– since a missing answer to that question would leave open a potentially serious situation

should such an allergy exist.

Comments from MOs about decision support related to electronic prescribing – not

surprisingly, as this has been a (yet unrealised) goal for hospitals for many years. MOs

translated the 'fit' to mean nature or format of the information, including: treatment options;

flagging drugs with a narrow therapeutic index; and drug interactions. The nature of support

mentioned by MOs was of two types: reference information (e.g. to underpin the detection of

drug-drug interactions); and patient-related support (using patient data, e.g. weight and age;

An ‘idiot’s guide to therapy’ will only ‘lead to individuals acting like idiots’

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and laboratory data, e.g. creatinine clearance, so as to flag cautions, such as the need to

modify dose).

It was suggested that this support should be: available when required; flexible; easy to use and

understand; and time efficient – essentially integrated into existing IT systems and daily

practice. However, if such a system was not easy to use (an experience some respondents

had already had with an existing clinical system), individuals would turn to 'non-IT' solutions.

Increasing experience (and knowledge) of MOs could also decrease the need for such

support. Some MOs felt that this type of support would decrease the reliance on the doctor to

detect some of these issues; and this was not desirable as there were so many patient factors

to consider. Interestingly, PDAs were not mentioned by MOs despite two of them having past

experience of PDAs.

5. 3.5.5 Is decision support a realistic expectation?Pharmacists were more pragmatic about whether ward-based decision support was a realistic

expectation. This was seen to be possible for prescribing, but less likely for other more

sophisticated support. For several pharmacists, this view was based on previous experience

with attempts to integrate hospital data systems (laboratory and pharmacy) for use with a DSS.

These attempts were considered too ambitious for the technology available at the time; and

these relatively unsophisticated data systems required complex algorithms for interpretation.

Similarly, a trial of PDAs in ward rounds had failed as the required information could not be

retrieved quickly enough.

MO's generally thought that DSS within the hospital scenario was a realistic option and

equated this with access – using PCs in the wards or clinical areas, bedside access, or using

PDAs. The notion of using PDAs as a gateway to a computer-based system came with the

expectation that all information should be available through these interfaces – participants

believed it would not be desirable to use PDAs to find part of the information required – and

then have to obtain the remainder of the information via a PC. Such an approach, of course,

would be extremely challenging – the MOs responding to this question were naturally thinking

in terms of user requirements, rather than the demands this would place upon the hospital itself

and on the developers of such systems.

5. 3.5.6 An ideal decision support tool?The researcher once again grouped responses into requirements categories based on

Pfleeger (1998). There were many overlapping concepts which were difficult to classify, as

answers expressed different levels of granularity (e.g. 'list of patient information' as opposed

(it) ‘all got bigger than Ben Hur’

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to 'medication list'); or similar but different meanings could be attributed to the terms used (e.g.

'validated' vs. 'accurate').

Again, MOs were predominantly concerned with data (especially format and type), whereas

pharmacists were more interested in quality assurance. This may indicate MOs' concern with

obtaining necessary information quickly whereas, for pharmacists, the reliability of data is the

critical issue. This latter observation stems from the fact that pharmacists frequently need to

interpret (medication-related) information for others, so that being able to have confidence in

their information sources is very important.

Both groups considered an information summary desirable, although more MOs wanted this

summary to be a gateway to other information – possibly reflecting the dependence of MOs on

a wider range of information than is the case for pharmacists, not only for treatment but also

for diagnosis. Participants acknowledged that a satisfactory trade-off between displaying

essential and all information would be difficult to achieve. One page was again suggested as

a target length for information, but of course, available page information on a computer screen

is very different from what can be provided on a single screen of a PDA. The issue of how to

compress sufficient information to make a single PDA screen useful was not, however,

discussed.

In contrast to summaries, one pharmacist preferred to use all information available, on the

basis that it was better to discern the value of the information for oneself, than to allow a system

designer or programmer to make that decision. This is, of course, the classic problem of

requirements engineering – without adequate communication between end users and analysts

it is impossible to ensure that the subsequent system will truly reflect the needs of those users.

This problem becomes still more complex when there are a variety of users, with differing

needs, who must be able to use the system under conditions of extreme urgency. It is therefore

not surprising that responses to this question indicated a considerable level of concern about

the effectiveness of such decision support systems in an acute care setting.

Replacing professional function was a further issue to be raised by pharmacists who saw little

value in simply replicating what they did in daily practice. They believed there was no need to

flag every minor interaction, but rather sought to identify important, patient-specific information

such as co-morbidities and biochemistry; especially for groups such as renal or cardiac

patients.

A significant issue which emerged from this discussion was that the availability of wider

information depended on 'someone' to enter it; and that reliance on information entered by

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others could present problems of reliability or timeliness. Also, as it was possible for

information to be incorrect, e.g. a diagnosis could often be incomplete, being a 'work in

progress' for the first few days of admission – respondents were uncertain how decision-

making could be supported against a background of varied and changing information.

As different health professionals view the same information differently, there is an issue of how

information can be structured to accommodate a variety of purposes or intents; one solution

might be to maintain the status quo – continue to share the same information. This not only

allows simplicity of design but also perhaps contributes to patient safety through using

'different eyes'.

5. 3.5.7 The acceptability of alerts and remindersAlerts and reminders were seen as one of the most positive features of a DSS. Seven MOs

believed alerts and reminders would be acceptable and could, indeed, be an avenue to

promote good prescribing practice. Nevertheless, they were quick to add qualifications: the

overriding feeling was that the number of prompts and alerts had the potential to be a

significant problem – too many would be a serious nuisance, leading to users ignoring all

alerts, e.g. constant reminders that a particular medication causes drowsiness. They

suggested that useful alerts would be those relating to toxicity (e.g. previous ADRs for a

patient), interacting medications/biochemical values (e.g. stopping potassium supplements if

the serum potassium was high), areas unfamiliar to the MO (e.g. drug contraindications in

pregnancy), or issues which required immediate attention. However, even serious reminders

would be a nuisance if they occurred too often; and the threshold at which they became an

irritation could (and probably would) vary for each individual doctor. There was a common

belief that alerts had to have some patient context to be of value – but tailoring alerts for each

drug, interaction and health possibility was recognised as difficult.

Generally, it was felt that the acceptability of alerts would be better if they were supported by

references (as to why they were important). This was regarded as good for inexperienced staff

or in an intensive care scenario, although it would obviously introduce an extra level of reading

and inconvenience (and would clutter up the screen – a major problem for PDA users). Once

again, importance, relevance and presentation remained major issues. One possible solution

would be to personalise such a system, so that more experienced MOs could limit the number

and frequency of alerts, although this issue was not discussed by participants. One MO

declared that justification of alerts would probably make no difference at all to acceptability.

Clinical support from information systems was seen as the ‘holy grail’ but difficulties in the past only provide cynicism about the ability to realise the real needs of clinician in an acute care environment

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5. 3.5.8 The acceptance of blocking medication ordersThis issue was raised with MOs rather 'tongue in cheek', with little expectation of a positive

response. Five MOs were against this idea and four were in favour – although the 'yes'

answers were really 'yes but .. ' responses. The many problems identified with the concept of

blocking medication orders included: the difficulty of obtaining complete patient information

within the system; the need to avoid delay in patient treatment; the possibility that there might

be no alternatives to treatment choice (even where there was a contraindication to the drug

prescribed); the unavoidable fact that there would always be exceptions to every rule; and the

awareness that medicine was 'so grey'.

Although it was acceptable that having a DSS block a medication order might be a safety

mechanism, e.g. for checking interns, in cases of previous serious ADRs or allergies, or where

absolute contraindications occurred, respondents felt that this could be very frustrating and

could waste time. Participants noted that, in any case, such blocks would quickly be

circumvented and individuals would resort to the paper system or the telephone if they

believed the medication was really needed.

Reliance on anything other than a perfect system was seen as a source of other problems.

Much of the decision support discussion, particularly that relating to electronic prescribing,

really related to expert systems1. At one boundary, a high level of decision support can be

provided using captured knowledge. However, capturing and structuring knowledge to allow a

complete representation of the patient in an information system is exceedingly difficult because

of the issues mentioned – missing information, information granularity; and the need for health

professionals to communicate.

Another very important factor is the extensive use of personal (tacit) knowledge by health

professionals in their clinical practice. This thesis makes no attempt to quantify such use, but

statements from pharmacists to the researcher indicated extensive use of personal knowledge

– this was the first strategy in responding to a question.

1. Expert systems are rule-based systems that attempt to model the human thought processes, based on sets of hypotheses (Thornett 2001, 'Computer decision support systems in general practice', Interna-tional Journal of Information Management, vol. 21, no. 1, 2, pp. 39-47).

It was: ‘hard to think of absolute circumstances where we should be definitely and consistently prevented from prescribing something’

(I) ‘use my own knowledge 95% of the time’

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Gaining this knowledge took many years and was fed by a range of formal sources (e.g.

undergraduate and post-graduate training, ward rounds etc.) and informal sources (e.g.

clinical experience, personal research and communications with other health professionals).

Clinical practice and personal experience were particularly significant. For example, clinical

ward rounds were important to allow a pharmacist to 'marry up the medical side with

medications' – this was of significant value in placing medication use into context. Over time,

recall of previous situations became the knowledge base for approaching new problems.

Communication with other health professionals also tapped into others’ tacit knowledge.

Further, 'systems' knowledge of the environment outside the hospital allowed pharmacists to

consider patient care more broadly than simply in terms of the consideration of immediate

medication use.

One knowledge-based approach to information gathering was akin to 'reverse engineering',

where the patient diagnosis was used to infer which medications the patient should be taking,

e.g. a patient with hypercholesterolaemia would normally be taking a statin (based on standard

clinical guidelines) – the absence of that medication would indicate a possible omission in the

current medication list or a need to recommend therapy. This of course, could be the role

undertaken by a DSS – but again this presumes a large amount of accurate, contextual clinical

information.

Thus, the knowledge level of these pharmacists made them 'specialist' practitioners; and some

were also approached as consultants in their areas of practice, both from inside and outside

the pharmacy. This specialist knowledge co-existed with the general knowledge held by

pharmacists. This general knowledge was also valuable to MOs, e.g. cardiology pharmacists

might be asked about antibiotic therapy by cardiologists during ward rounds as cardiologists

would be familiar with 'their own' drugs but not antibiotics.

In summary, the enormous difficulty of capturing knowledge for a DSS ('expert system') and

the need for pharmacists and MOs to make use of their personal knowledge in dealing with

patients suggested a particular approach to the design of a decision support tool – providing

'essential' information and relying on a complement of human knowledge. The answer to

providing a practical technology tool for medication management seemed therefore to lie in

designing a system for experts, rather than an expert system.

5. 3.6 Complementary and Over-the-Counter medicationAlthough complementary medicines (CMs) and over-the-counter (OTC) preparations were not

specifically targeted by the researcher, it became clear that this area is a notable omission in

the information sought by pharmacists and MOs. Patients did not mention this group of

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medications often, nor bring them in to hospital – and neither MOs nor pharmacists asked

about them routinely. This was a surprising and disappointing lacuna, in light of the fact that

(certainly with CMs) there is increasing discussion in the medical literature about the potential

for interactions with prescribed medications against a background of growing use.

Discussions and observations revealed that CMs only came to mind in particular clinical

scenarios, e.g. with ‘hepatotoxicity of unknown origin’, or ‘funny neurologic (sic) symptoms and

seizures’, where this information might be vital for patient management.

However, this lack also presents an opportunity. As a goal of this project was to develop a

flexible approach for capturing medication information, the tool developed accommodates the

recording of CMs and OTCs, as well as prescription medications. Once recorded, instances in

the record would further serve to remind other health professionals to enquire about this group

of medications, thus providing a pathway for a complete medication record.

The recognition of themes from analysis of the questionnaire, interviews and work practice

observations provided the researcher with some fundamental concepts of medication-related

information use and approaches for dealing with this use. The final part of the data evaluation

process was document analysis, completing the picture of what information was essential to

medication-related decision-making. This is discussed in the next sub-section.

5. 3.7 Document analysisThe complete analysis of information components from document is shown in Appendix J.

These were modelled by the researcher using Unified Modelling Language (UML). The model,

shown in Figure 5-2, includes the frequency counts (in brackets) of the information

components.

Often a ‘blind eye’ was turned to complementary medicines

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The nature of the information components suggested initial categorisation under three main

information headings: patient, medication and laboratory. Not all components of all documents

were included in this analysis: some items were omitted because they were not components

per se, e.g. pharmacists use of a report from the hospital dispensing system, containing the

drugs and quantities dispensed for a patient – this report was a composite of information

elements that could be contained the model, rather that the report being an element itself.

Others, e.g. pharmacist names, doctor names and dates at the bottom of documents were not

considered important for the modelling exercise. Similarly, some inpatient drug chart details,

such as nurse administration codes, were too specific and were therefore omitted. Other

components (e.g. adverse drug reactions), despite having few occurrences, were represented

because they are so important.

Thus, the document analysis was not intended to be either an extensive or an exhaustive audit

which would capture every single information component that could be included in a hospital

patient case note – however, most components were represented. Some components

required a decision between alternatives. For example, medication components in inpatient

charts consisted of separate generic/brand name, dose, route and frequency elements. For

Figure 5-2: The information model from document analysis

Medication management document (occasions = 52)

Patient information Medication information Laboratory

Patient sticker (18)

Personal Reference

Name (38)

Address (7)

Patient record ID (34)

Date of Birth (27)

Age (11)

Sex (16)

Weight (4)

Height (2)

Internal

Allergies / sensitivities (13)

Adverse drug reactions (1)

External

GP details (4)

Community Pharmacy (3)

Reason for admission /Principal diagnosis (14)

Past medical history (7)

Lab. Comment (1)

Lab. test Date (3)

Lab. report Date (2)

Basic information Additional information

Medication managementIssues (3)

Ceased / changedDate (2)

Reasons summary fordose change (3)

Person responsiblefor change (2)

Start date (5)

Name (generic / brand)

Dose

Route

Frequency

AdditionalInstructions (7)

Supply source (3)

Duration ofTreatment (3)

Reconciliation of D/C or admit drugs (3)

Social History (4)

Others (9)

Discharge date (6)

Admit date (8)

Medical team (8)

Ward /cost centre (14)

Clinic (3)

Days in hospital (3)

Observations (1)

Observation dates (2)

Referral date (1)

Problem / action& outcome list (3)

Finish date (1)

Bed no. (1)

Progress summary (1)

Interview date (1)

Alcohol / drug history (1)

Administration date (2)

Warnings (1)

Person responsiblefor administration (2)

Administration aids (2)

Pharmacist contact (1)

Prescriber contact (1)

Information source(of medication history) (1)

Page 155

others (e.g. patient medication cards, medication lists in case notes) there was no separation,

i.e. all this information was usually combined in a single text phrase. It was also noted that

medication lists/cards for patient use were divided into 'regular' medications and 'when

required' medications; and could have separate columns for morning, midday, evening and

bedtime doses. The researcher chose to model the individual items separately, as this seemed

likely to provide a better basis for broad use within both hospitals and the community.

Formulation of the information model now began, and included the missing (and fundamentally

important) information components confirmed from interviews and work practice observation,

which were compared with high frequency information components identified from the

document analysis. This combination suggested the essential components which became the

basis of the initial information model, described in Section 5.4.

5.4 Formulation of the information modelThe first step towards development of the information model was construction of a qualitative

model, using nVivo, to provide a hierarchical view of the missing information components

observed in practice – shown in Figure 5-3. The main category nodes are shown in dark blue;

and instances within these categories are shown as pale blue nodes (without any quantitative

measures). Bracketed numbers under some of the nodes are not descriptive of node attributes

but merely indicate the node reference within nVivo. The main purpose of this exercise was to

group the information components which were important in themselves, or essential to

medication-related decision-making.

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The refined model subsequently developed by the researcher is shown in Figure 5-4. This

contained four major categories of information: patient, treatment, medication and

investigations. Patient information contained review date, and personal and reference

information; treatment consisted of current treatment and history; medication information

contained current medications, medication history and medication management issues; and

investigations contained laboratory tests. The reason for the investigation level above

laboratory values was that although laboratory (e.g. drug or electrolyte) results were the most

commonly mentioned tests requested on patients, other investigations were also possible (e.g.

from AH professionals). This separation allowed for future flexibility in the model.

UML was selected as the representation method because it provided a means of mapping

components which needed to be implemented in the digital document. There was, however,

no code generation from the UML model, although of course this could be a basis for later

implementations of this model

So by the end of data analysis, an essential information model was formed that could support

a technology approach to help with the management of medication information in the hospital

Figure 5-4: The hospital information model

Medication management document

Patient information Treatment information Medication information Investigations

Date of review Personal Reference

Name

Address

Patient record ID

Date of Birth

Age

Sex

Weight

Height

Recent BP

Allergies / sensitivities

Adverse drug reactions

Recreational substance use

GP details

Community pharmacy

Current treatment

Reason for admission /Principal diagnosis

Active problem

Treatment History

Past medical history

Laboratory

Date

Item

Result

Currentmedications

Medicationhistory

Medicationmanagement

issues

Ceased / changed

date

Reasons fordose change

Person responsiblefor change

Medication

Date

Generic name

Brand name(s)

Dose

Route

Frequency

Additionalinstructions

Indication

Duration oftreatment

Patient indication

Maximumdose

Social history

Complianceissues

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setting – answering question A. The next section (Section 5.5) addresses this technology

approach to the digital document, which answers Question B.

5.5 The digital documentThe researcher chose XForms technology because it appeared to offer a number of technical

advantages for the development of a document-oriented view of (XML) data. For brevity's

sake, it is not possible to detail all the aspects of development and implementation – these can

be found in the various appendices mentioned at the beginning of this chapter (see Table 5-

1). The approach to this section will therefore be to 'walk through' development and

demonstrate the major steps and outcomes of the process. Similarly, not all screen shots will

be shown within this chapter, but rather those representative of the different faces of the digital

document.

5. 5.1 Some preliminary activitiesThere were two preliminary activities undertaken by the researcher prior to the development

of the digital document.

The first activity was an introduction to XForms technology. This involved using a server

implementation of XForms technology using an experimental medication-related information

model based on the researcher’s domain experience. This activity is reported in more detail in

Appendix K.

The second activity was concerned with what browser platform was going to be used in the

project to display the XForms document. This activity concluded that a suitable browser for the

display of the XForms document was Microsoft Internet Explorer® (IE) 6, together with a

required ‘plugin’ – formsPlayer® (x-port.net Ltd.). Formsplayer is responsible for the display of

the fP ( ) icons that will be subsequently seen in the screen shots of the digital document

in this thesis.

A further realisation was that there was a need to provide a user with file-related functions i.e.

for the digital document to be used with a variety of patient files. File-related functions were not

able to be implemented within the XForms document – this could only be done in a server

environment, creating a problem for ‘local’ use of the XForms document on e.g. a notebook

computer. This was solved by developing a very simple browser application using Microsoft

Visual Basic® (Version 5, Learning Edition), shown in Figure 5-5. This Visual Basic (VB)

browser provided functions to: view existing patient files, open patient files, add new patients

and close the browser. At this stage of the project, there was no need for a more sophisticated

environment as all that was required was a simple stand-alone application. The complete

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details about the VB browser are available in Appendix K.

5. 5.2 Developing the digital documentThe approach taken to implementing the digital document was that it should resemble a

conventional paper document as much as possible – avoiding (if possible) display elements

found in databases, such as grid elements and function buttons. The resultant ‘look’ of the

digital document was simple and ‘flat’ – similar to paper documents. Unfortunately, this ‘look’

was not able to be carried through to the sub-components of the digital document that were

used for data entry (i.e. data entry forms), however these forms were kept small to minimise

screen complexity for the user.

The translation of the information model to the digital document was based on each major

information category in the model being a separate ‘page’ in the digital document. Therefore,

e.g. the patient information node in the information model became the patient information

‘page’ in the digital document; and the elements within the patient information node (e.g. name,

address etc.) became information elements in the patient information page. This principle was

Figure 5-5: Visual Basic document viewer

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used for the other major information categories in the information model. This provided a good

alignment of the information model with document representation, which allowed changes in

the information model to be easily reflected in the digital document. The document could also

be described to participants as having tabbed pages – another paper metaphor familiar to

users e.g. an alphabetically indexed address book. There was a further advantage in using

tabbed pages as users would not need to scroll through an extra-ordinary long single page

document.

Minimising scrolling was also an aim within each document page – this led to the removal of

GP and pharmacy details from the front page of the document to a separate page. Although

not strictly in keeping with the information model, these components would not be used as

often as others would. (This pragmatic decision was later supported by pharmacist participants

during bench-top testing)

In keeping with the intent to not impede the work process, no fields were made mandatory as

the user should not be forced to enter anything as, of course, they might not possess this

information. A summary description of each page is provided in the subsections which follow.

5. 5.2.1 Patient details pageThe patient details page is shown in Figure 5-6. Information components for this page include:

patient name, address, Medicare number, date of birth and age (either could be entered), sex,

weight, height, blood pressure (systolic and diastolic values); and date of medication review.

When a value for weight, height or blood pressure was entered, XForms functions were used

to calculate the number of days since this took place (shown in blue). Flags could also be

displayed (the Omega symbol) if the difference was greater than 90 days. Using a similar

function, if the weight was missing, then the word ‘Missing’ would be displayed in lieu of the

weight value. These are examples of the dynamic functions available within XForms which can

be used to provide simple alerts and reminders.

Editing patient information required clicking on ‘edit personal details’. This opened a separate

form displayed in Figure 5-7. Hyperlinks were not underlined (as is the convention) to make

the document appear as much as possible like a paper document. Users were alerted to a link

when the cursor arrow changed to a hand-shaped cursor as the mouse pointer moved over

these links.

Allergies and adverse drug reactions were displayed as separate information groups, as

suggested by the model. The reason for this is that allergies are pharmacologically distinct (to

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ADRs) as they have an immunological basis, with a particular pattern of symptoms.

Recreational drug use (as defined by pharmacists) relates mainly to tobacco and alcohol

(although it is clearly not limited to those agents alone). The display of the editing options under

those groups uses the same style to maintain visual consistency and ease of use. This style

was maintained throughout the document as much as possible.

One feature that is common to all lists is colour highlighting of the line of information that has

current focus. For example, in Figure 5-6, the peanut allergy record has the current focus and

is shown in violet (as opposed to the amoxycillin record below coloured in black). This is also

Figure 5-6: Patient details page

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confirmed by the row number displayed next to the word ‘edit allergy’. The reason for both

these choices is that the coloured line is more immediately obvious. However, when display

on a monitor is less than optimal (e.g. one some notebook computers) or could influenced by

environmental lighting, the number proved to be more useful. The colour violet was selected

for use in the document simply because it complemented the violet colour of the fP logo.

The new allergy edit form is shown in Figure 5-8. The data entry fields are either text or, in the

case of Reaction date, xsd: these are formatted fields as defined by XForms 1.0. The

advantage of using date formatted fields was the availability of a drop-down calendar object

with the ability to do date arithmetic which this provided. Invalid values (e.g. the date in Figure

5-8) were flagged using violet bars to the right-hand side of the field.

Figure 5-7: Edit patient details form

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5. 5.2.2 Treatment information pageFigure 5-9 shows the simple treatment information page which displays principal diagnoses

(responsible for the patient’s hospital admission) and other active problems. This page

demonstrates the concept of a simple summary, suggested by participants being able

themselves to provide patient context – in this case, name of the condition and time frame. This

simplified representation was applied to other similar information components within other

pages.

Figure 5-8: New allergy form

Figure 5-9: Treatment information page

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5. 5.2.3 Medication information pageAlthough the medication page (Figure 5-10) is also displayed in a simple manner, there is

greater underlying complexity to this page.

The medication information components comprise: date (relating to supply or when first

recorded – the difference is not really important as the intention is to initially capture the use of

the medication at some point in time and establish a reference point); name (either generic or

brand); dose; route; frequency; instructions; indications (from the prescriber); duration; and

maximum dose (where appropriate). Although some of these components (e.g. indications or

duration) are not usually included on hospital prescriptions, this information which is normally

available from patient case notes, was considered important by pharmacists.

The medication editing forms are more complex as they contain more information components.

The edit medication form is shown in Figure 5-11; and the new medication form is shown in

Figure 5-12.

Figure 5-10: Medication page

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There is one significant difference between the edit and new medication forms – the edit form

also has fields for reason for change, by and date. When the edited information is saved, this

not only changes the current medication record, but also copies the information to a separate

section of the patient file containing the medication history. Capturing medication history (an

expressed information need) is thus supplemented by knowing why this was done, by whom

and when – providing a much better context for medication use.

Figure 5-11: Edit medication form

Figure 5-12: New medication form

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The medication history information display is displayed below the current medication

information after clicking on ‘view medication history’, shown in Figure 5-13. In the example,

the current medication is amoxycillin capsules 500mg. The previous dose was amoxycillin

capsules 250mg, shown as the bottom entry in medication history. The most recent medication

history item shows the current dose and the reason for change (‘dose increased’ by ‘jpc’ on

2006-08-28). Return to the previous display is by clicking ‘back to current medication’.

Medication-related issues, either Social or Compliance-related were implemented as two

simple text boxes, again on the basis that simple text would be the most flexible and expressive

(and thus most efficient) way of conveying information which could relate to a large number of

issues. These required only a simple editing box. The edit social issues form is shown in

Figure 5-14.

Figure 5-13: Medication history

Figure 5-14: Edit social issues form

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5. 5.2.4 Investigations pageThe investigations page (Figure 5-15) is as simple as the Treatment Information page;

including the information items: item, result and date of result. Item has been purposely left

generic and can represent a blood result value (e.g. serum potassium, blood sugar level, INR)

or radiological report text – again is to support a summary concept. The expectation was also

that not all values needed to be entered, only those considered important to a decision.

5. 5.2.5 Health Professional contacts pageAs already mentioned, health professional contacts were initially part of the patient information

components, but since they are not frequently used, were moved ‘to the side’. This page is

shown in Figure 5-16.

Figure 5-15: Investigations page

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5. 5.3 Experiences with XFormsAlthough XForms allowed quite rapid development (after the initial learning curve), the

researcher encountered a range of problems and issues quite early on.

These issues included:

• the lack of a dedicated XForms editor

• the lack of practical documentation (texts or examples) that could help with implementing

some of the required features in the digital document

• problems with different versions of the browser plugin (formsPlayer)

• the level of implementation of the XForms 1.0 standard in formsPlayer

• inconsistencies between how XForms and IE 6 interpreted Cascading Style Sheets,

causing problems with display of some elements in the digital document

• limitations with some of the functions supported by XForms.

In the last case of the issues presented, date functionality was a particular problem that

required some accommodation from users of the digital document. These issues are

presented in some detail in Appendix K.

Figure 5-16: Health professional contacts page

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5.6 Chapter summaryThis chapter reported the hospital scenario investigation that aimed to answer two research

questions – these are addressed consecutively below.


The strategy used to answer this first question was an investigation of information use by

pharmacists and MOs involved in medication management. Data triangulation of

questionnaires/interviews, work practice observations and document analysis allowed a

thorough examination of the type and nature of information components that were used.

Analysis of the data revealed a number of important themes that influenced the researcher’s

approach to developing the information model.

Missing information in the hospital scenario was common, particularly for medication-related

information; and was a potential problem for patient outcomes. This problem has major

implications for the successful implementation of decision support systems. However, in this

project, the researcher based whether pharmacists pursued missing information as a

surrogate for its value to the decision-making process; and subsequently inclusion in the

information model.

Information use by pharmacists MOs was also characterised by the need to use different types

of disparate sources of information, based on the decision-making context and the personal

knowledge of the individual. This ranged from patient case notes to specific data items such

as a laboratory value, i.e. from aggregate to singular, which has significant implications for the

representation of information in clinical systems. As information needs were reported at

different levels of granularity, this should be reflected in the consequent information model.

However, this represents a tension for the design of health information system – the need to

have atomic data to build decision support systems and support research, against the need to

efficiently communicate and share contextual information for patient care.

Conversation with other health professionals was a common method of obtaining information

that was missing from expected sources, but also when other multiple sources were available.

The importance of conversation was that it was a highly contextual and efficient means of

information transfer between health professionals, allowing access to tacit knowledge; and it

has other roles that cannot be mimicked by decision support tools. In light of this and the strong

desire for health professionals to communicate, the decision support solution needs to be one

that supports, or at least does not hinder this desire.

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Time was raised as a significant issue affecting the ability to interact with a decision support

tool. However, using a relevant, concise information summary as the interface to a decision

support tool was seen as part of a possible solution to this issue.

The investigation of decision support tools used in the hospital found that those in use were

generally unsophisticated; and this also influenced perceptions of what an ‘ideal’ decision

support system should be. Despite agreement that these systems promised benefits, there

was widespread acknowledgement of the difficulty of implementing them and the barriers to

their use – supported by poor experiences in the past; and cynicism as to whether there would

be much success.

The researcher came to the conclusion that in light of the many issues uncovered above; and

the significant reliance of personal knowledge in clinical practice, this suggested that the

approach to design should consider systems for experts rather than expert systems – a

complement to human knowledge rather than attempt to model it completely. The final theme

was that of the inattention paid to complementary medicines and over-the-counter

preparations, possibly an opportunity for the digital document in practice.

The many difficulties experienced by pharmacists and doctors with medication management

suggested that technology could address these issues through a shareable model of essential

information components. This model would need to cope with missing information components

and acknowledge the use of knowledge.


This question was addressed by investigating the potential for XForms technology to realise

the digital document based on the information model identified for medication management.

XForms was selected as the underlying implementation technology based on the technical

advantages it offered, while using a document-oriented view. Development was made difficult

however, by a lack of practical supporting documentation, the level of standards

implementation in the formsPlayer browser plug-in; and the limited ability of some XForms

functions, particularly handing dates. However, the digital document prototype was developed

with XForms as intended; and this paved the way for the next phase – testing the information

model (through the document artefact) to measure its suitability for the community. This was

done through bench top testing with pharmacists accredited to carry out home medication

reviews in the community; and is described in Chapter 6.

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Chapter 6

Modelling for the community context: benchtoptesting

6.1 Introduction Chapter 5 described the first investigation scenario in the hospital setting; and the

development of the first information model and digital document prototype.

Although there was an expectation that many fundamental elements would be common to both

the hospital and wider community contexts, the information model required some modification

in order to fit the wider community. This modification took place during the second iteration; the

benchtop testing of the prototype. The empirical research undertaken in this phase sought to

answer the next research question:


This question was addressed as Part 2A of the project and involved: benchtop testing by

pharmacists accredited to perform home medication reviews (HMRs); further probing of the

questions explored in the hospital scenario; and some more focused questions about the

technology used to support HMRs.

This chapter reveals the differences in information requirements and use for accredited

pharmacists in the community. Themes which; emerged in the hospital context are also

examined here; and new themes identified. The full analysis of the data from this scenario is

contained in Appendix O. Full technical details for this chapter are contained in separate

appendices as shown in Table 6-1.

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• the ways in which the data were gathered is reported in Section 6.2

• analysis of the data is presented under the themes that are relevant to this scenario in

Section 6.3 – this provides consistency with the approach taken in chapter 5 and also

allows comparisons to be made with the hospital scenario

• changes that resulted in the revised, community-aligned information model are

discussed in Section 6.4

• the changes made to the digital document; and the development of the server service

are detailed in Section 6.5, and;


6.2 The data gathering processData gathering for the benchtop testing phase of the research included four separate

processes: firstly, a series of questionnaires and interviews with pharmacists accredited to

conduct HMRs; followed by testing of the prototype with this group of pharmacists; thirdly, a

focus group conducted with 3 members of this group, to enable a deeper and richer exploration

of issues arising out of the first two phases; and, finally, a detailed examination of relevant

documents – as was done in the initial, hospital-based, phase of exploration.

6. 2.1 Questionnaires and interviewsPotential participants for this scenario were identified by the researcher either as a result of

nominations made by Pharmacist Facilitators of the Divisions of General Practice, or during

discussions in the hospital scenario. The researcher approached the potential participants

directly and if they agreed to participate, the researcher sent them a questionnaire to them by

email or mail; and made an appointment made for an interview. The XForms document (and

formsPlayer plugin) was installed on participants’ computers – at the interview if possible or, if

not, during a subsequent meeting.


Appendix Content

P Full technical and development details.

Q Prototype development record (spreadsheet).

R Visual Basic (VB) browser code.

S Server (ASP) code.

T XForms document code.

U Patient XML file structure.

V XSL (report) code.

W Comparisons of information model elements (spreadsheet).

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This part of the study began in early 2005 and was completed in October 2005. Overall, six

pharmacists agreed to be involved. Pharmacists’ experience ranged from 5–32 years of

general practice (average 19.5 years), with 2–8 years of Home Medication Review (HMR)

experience (average 6.7 years).

6. 2.2 Prototype testingAs with the hospital scenario, the interviews provided an understanding of what information

was used, what was missing and what was desired to support medication management – or,

in this specific case, HMRs. Pharmacists testing the prototype with previous patient cases

would confirm the real information needs for those cases which offered parallels to the work

practice observations made in the hospital during the previous empirical research phase. Each

pharmacist was asked to enter five previous HMR patient cases into the digital document. The

researcher was able to observe two pharmacists, but time constraints made it impossible to

observe all five pharmacists during this phase of the research. Patient data was not viewed by

the researcher to maintain privacy.

As HMRs are a relatively new practice area for community pharmacists, the next two

subsections of this chapter provide some background about the skills of these pharmacists and

what the HMR process generally entails.

6. 2.2.1 Accredited pharmacistsPharmacists permitted to conduct medication reviews in the home or in Aged Care Facilities

(ACFs) are known in Australia as 'accredited pharmacists' (although the term 'consultant

pharmacist' is occasionally used). These pharmacists are accredited by the Australian

Association of Consultant Pharmacy (AACP) or the Society of Hospital Pharmacist of Australia

(SHPA). This accreditation not only ensures that these pharmacists have the additional skills

and knowledge required for undertaking medication reviews, but also allows them to claim

remuneration for their service from Medicare1.

Accreditation for pharmacists to undertake medication reviews in ACFs was first recognised in

1997; and this was extended to allow HMRs in 20002. HMRs were initially called Domiciliary

Medication Management Reviews (DMMRs) and although both terms are still in use, the more

recent term HMR will be used throughout this project. Similarly, the terms aged care facility

and residential care facility are used synonymously within the community, but the researcher

will use the term aged care facility (ACF). Without wishing to confuse the issue of acronyms

still further, medication reviews undertaken at an ACF are commonly referred to as Residential

Medication Management Reviews (RMMRs) – and this term will be used for this particular

1. Medicare is Australia’s universal public health system2. Personal communication, Sue Edwards, Pharmacy HMR Facilitator, 5/9/2006.

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category of medication reviews within this thesis.

6. 2.2.2 The HMR processThe goal of the HMR, according to the Australian Department of Health and Ageing, is to

maximise an individual patient's benefit from their medication regimen. Accordingly, the

Department has produced HMR guidelines for General Practitioners (GPs) undertaking HMRs

(http://www.health.gov.au/internet/wcms/publishing.nsf/content/health-epc-dmmr.htm/$FILE/

dmmrfactsheet.pdf; viewed 2006-09-12). This process is summarised in Figure 6-1, although

a more detailed description is contained in Appendix O.

By its very nature, the HMR process targets the elderly and/or individuals with chronic disease

who tend to have complex medication regimens – the disease groups of main concern in

medication management are cardiovascular disease, coronary heart failure and diabetes.

These individuals are at high risk of adverse events because of the complexity of their disease

processes or medications, or both. Medication management for patients at ACFs can still be

more difficult as these patients’ problems can be complicated by dementia and/or other self-

management issues (often the reason they are residents in an ACF).

As already noted in Section 6.2.2.1, the term ‘accredited pharmacist’ is the correct title for

pharmacists accredited to undertake medication reviews. The term ‘HMR pharmacist’ will

Figure 6-1: Home medication review process

HMR need identified(patient, carer, pharmacist,

other)Patient consent obtained

HMR referral form / relevant information sent to patient’s

preferred community pharmacy

Accredited Pharmacist conducts HMR

Pharmacist completes HMR report

GP develops draft medication management plan.Arranges follow-up

consultation with patient

GP & patient meet and agree on medication management plan

Copy of medication management plan to pharmacy,

Copy to GP & +/- copies to patient / other relevant health

professionals with patient agreement

Implementation of agreed actions with appropriate follow-

up and monitoring

HMR report sent to GP

Preferred pharmacy

Optional

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however, be used in this chapter – both because this term links the pharmacist to the process

undertaken, as well as to avoid confusion with a different medication review process which will

be described in Chapter 7.

HMR pharmacists consider their roles to be primarily focused upon patient education and the

optimisation of drug use (QUM) – a similar perception to that of their hospital colleagues. One

difference, however, is that the HMR pharmacist aims to identify any outstanding issues,

whereas for hospital patients, many issues already have been identified (or even have been

the reason for admission to hospital). A significant concern of HMR pharmacists was patients’

self-management, as this was important for patient independence, successful therapy and

safety. Respondents placed a significant emphasis on a holistic approach to patient care and,

with elderly patients in particular, believed that quality of life could often be more important than

specific management issues for medications or disease.

6. 2.3 The focus groupThe focus group enabled the participating pharmacists to come together after the benchtop

testing was complete, to share and describe their experiences of interacting with the digital

document. As already explained in Chapter 3 (Methodology), the group was moderated by the

researcher, as his domain experience provided allowed a level of understanding of hospital

and community pharmacy practice which could be used to stimulate discussion in a way which

would not have been possible for a less experienced moderator; as well as to improve the

quality of the data collection. In addition, as the focus group was small (3 pharmacists), data

collection could be achieved effectively through audio-taping, without requiring the researcher

to focus on note taking, at the expense of coordinating the group.

6. 2.4 Document analysisAs with the hospital scenario, document analysis was intended to uncover all the possible

information elements used by the participants. This task was simpler than was the case with

the hospital scenario, partly because there were fewer participants, but also because the range

of documents was smaller. Four of the five pharmacists supplied an example of their HMR

reports but, as this only provided a small number of samples, the researcher also sought

further representative HMR documents from other appropriate sources. This is detailed in

Sub-section 6.3.11.

6.3 Analysis and discussionThis section analyses and discusses the data from all sources: questionnaires and interviews,

prototype testing, the focus group; and document analysis. As with the previous chapter, in

order to keep the discussion to a manageable length, the detailed analysis and data collection

tools (pharmacist questionnaires, focus group tool etc.) are contained in appendices.

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Table 6-2 summarises the location of this information.

The questionnaires used for HMR pharmacists contained many of the same questions used

with hospital pharmacists to enable comparison of common issues. A further set of questions

was also applied to elucidate HMR workflow and the technology used by HMR pharmacists,

as this could impact on how the digital document might be implemented in the community

setting.

The set of questions used with HMR pharmacists is shown in Table 6-3.

Table 6-2: Data-related appendices

Appendix Content

Appendix F Data collection tools.

Appendix 0 Analysis of benchtop data.

Table 6-3: Questions posed to HMR pharmacists

Main questions

What do you think are the main aims of a HMR pharmacists' role?

What do you think are the main goals in medication management?


Can you describe your relationships with other health professionals in achieving patient care goals?

What are the information sources you use in your work practice for patient medication management?

Have you ever needed to obtain information from sources other than in your practice environment? (what, when, how and for what?)

Do you use any other (personal) knowledge in addition to information sources as part of your decision-making? If so, please provide detail of the nature of the knowledge and how you acquired this knowledge.

Are there any information components that are missing (if so, is this often?)

How do you manage with missing information components?

Do you think there are there any implications for medication management?

Do you think there are there any implications for patient care or patient outcomes?

Are there any decision support tools in place to help with medication management?

What is your understanding of the term 'decision support'?

What would expect from an 'ideal' decision support tool?

How would you expect it to fit in to your work practice?

Is this a realistic expectation in your current work scenario? (please give reasons)

Workflow & Technology

How is the HMR request is received?

How is the HMR request processed (including any information transfer)?

What is the process for conducting HMR?

What is the process for report writing?

What is the process for the delivery of the report to the GP?

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Analysis of the data and discussion is, as in Chapter 5, grouped under the same themes

developed for the hospital scenario. The majority of the themes identified in the hospital

scenario were also relevant to the HMR pharmacists, although two new themes emerged

which were unique to this scenario. This result not only provided support for the findings from

the hospital scenario, but also identified the specific factors relevant to the community

scenario. This variation, anticipated by the researcher in light of his own clinical experience,

was crucial in terms of developing the digital document and ensuring its acceptability within the

community context – a medication management solution which only supported in-hospital use

would clearly be of only limited usefulness.

Prototype testing and document analysis are discussed separately. The themes and their

respective sections are shown in Table 6-4.

6. 3.1 Missing information

6. 3.1.1 Missing information for HMR pharmacists in GPs’ referralsThe problem of missing information was even more significant for HMR pharmacists than it had

been for hospital pharmacists. Whereas a hospital pharmacist had access to alternative

information sources, HMR pharmacists were able to rely on only two information sources: the

HMR referral from the GP and, optionally, a printout of the patient's medications dispensed by

their preferred pharmacy.

The amount of missing information within referrals used by HMR pharmacists was also

significant. Laboratory information was generally missing and, in some cases, this information

could be important e.g. information about renal function if the patient was taking metformin

(used in the treatment of Type II diabetes). Other potentially useful information which could be

missing included: the reasons for medication changes; patients' co-morbidities; whether a


Section Theme

6.3.1 Missing information

6.3.2 Information granularity

6.3.3 Conversation and communication

6.3.4 Time constraints and summary information

6.3.5 Decision support tools

6.3.6 Systems for experts rather than expert systems

6.3.7 A technology-poor practice paradigm

6.3.8 The ‘viewpoints’ of professional practice tools

6.3.9 Pharmacists’ perceptions of GPs in the HMR process

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medication had been tried and failed in a patient; and patients' drug sensitivities. Information

about the social situation or environment (e.g. was there a son with psychiatric problems, or a

potentially dangerous dog, at the patient's home?) could be important for pharmacist safety –

one pharmacist mentioned having been in an unsafe situation during an HMR interview with a

patient.

One potentially missing information component which generated a great deal of discussion

was the ‘real’ reason for referral. The reasons for referral usually given by the GP were one or

more of the risk factors for adverse outcomes for patients taking medications, shown in Table

6-5, provided as examples by the Health Insurance Commission (HIC)1.

These risk factors could, of course, be valid reasons for review. The HIC had originally

intended these risk factors merely as a guide for physicians, but they had instead become de

facto bases for GPs' HMR referrals. The pharmacists believed that these risk factors were

used by GPs as a 'pick list' to appease the HIC system and thus ensure payment for the HMR

referral. Pharmacists were concerned that sometimes these reasons did not indicate the real

reasons for the GP's concern (e.g. unstable INR levels for a patient). The lack of a more

targeted reason could mean that the real problem was not investigated and, consequently, not

appropriately reported back to the GP. The HIC guidelines are quite open (although this is

obviously not known by GPs), as a GP can initiate an HMR if it is clinically necessary to 'ensure

the quality use of medicines or to address a patient's needs' (http://

www.medicareaustralia.gov.au/providers/incentives_allowances/pharmacy_agreement/hmr/

patient_eligibility.htm; viewed 2006-09-10), i.e. if there is any concern about the patient's ability

to manage medication at home.

Overall, pharmacists felt they could place only precarious reliance on the GP to provide the

appropriate information for the HMR. One pharmacist stated that if, for example, pathology

1. The Health Insurance Commission is the Australian Federal government agency which pays GPs and pharmacists for HMRs.

Table 6-5: Risk factors for adverse outcomes for patients taking medications

Risk factor

Currently taking five or more regular medications, or more than 12 doses of medication per day.

Significant changes to the medication regimen in the last three months, including recent discharge from hospital.

Taking medication with a narrow therapeutic index or requiring therapeutic monitoring.

Symptoms suggestive of an adverse drug reaction.

Difficulty managing own medicines because of literacy or language difficulties, or impaired sight.

Attending a number of different doctors, both general practitioners and specialists.

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information was not provided in the referral, it was assumed the GP might not need feedback

in this area. This rationalisation is understandable, but does raise concern about the

effectiveness and consequent usefulness of an HMR.

6. 3.1.2 Pharmacists coping with missing information

Although the medication-related information from the GP could be ’scant’, pharmacists did not

usually contact the GP unless there was a ‘burning need’ to do so. Pharmacists could use the

local pharmacy to try and fill information gaps; and they routinely sought records of patients’

dispensed medications from the community pharmacy. Some pharmacists, indeed, expressed

rather pragmatic and pessimistic views about contacting GPs. In this rather precarious

situation, pharmacists often assumed that the GP might already possess the missing piece of

information (so pharmacists did not need to obtain it), or believed that the GP might have

already addressed the issue of concern. However, a contrasting view from one pharmacist was

that: ‘often things don't fall into place until you ask the GP later’.

This lack of information was taken into account by pharmacists when writing the HMR report;

and most pharmacists incorporated a disclaimer such as:

These comments are made without the full knowledge of (name)’s medical history. Any treatment decisions based on this information should be made in the context of the individual clinical circumstances of the patient.

The end result of missing information and the (possibly perceived) communication difficulties

between pharmacists and GPs was that the HMR report might well not be as useful to the GP

as it could be. This problem was addressed by pharmacists on the HMR report, by raising

issues which needed to be considered by the GP; and adding disclaimers to indicate that

recommendations were made without full knowledge of the patient.

Of course, the issue of missing information clearly depended on its type: some missing

information (e.g. date of birth) could be obtained by the pharmacist from the patient at the

interview, although (as in the hospital scenario), patients could be unreliable about their

medications. Obtaining some information could be especially difficult for the pharmacist, e.g.

patient weight (some pharmacists actually carried a set of bathroom scales with them to HMR

visits to weigh patients – not always an easy undertaking!). It became clear to the researcher

that pharmacists' skills were particularly important. Ensuring that they asked the right

questions and the ability to 'read' patients were important skills which improved over time – as

was the ability to gauge when there was no need to ask questions. A great deal of information

could also 'reveal itself in the home' e.g. if the blinds were pulled down or the carpet was torn,

(if the) ‘GP provided information is scant... then perhaps they are not interested in providing it’

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the pharmacist could infer a potential risk of patient falls.

6. 3.1.3 The implications of missing information

Pharmacists considered the main implication of missing information for medication

management was the quality and consequent usefulness of the HMR report to the GP. Missing

information meant that the review was not as comprehensive as it could have been, because

the right questions might not have been asked (of the patient) – and because a better

understanding of the reasons for the HMR referral might have avoided the need to ask

unnecessary questions.

Pharmacists expressed some pragmatic resignations about the effectiveness of highlighting

issues in an HMR report to the GP. In one example, where the metformin dose was high and

there was no indication of renal function, the pharmacist recommended (depending on the

patient's renal function) that a drop in the dose of metformin could be considered, or a newer

oral hypoglycaemic agent (more appropriate for renal problems) might be added. The patient's

dose of metformin was indeed dropped for a short while, but was then increased again without

(apparent) consideration of the newer agents, leaving the pharmacist with no idea at all of the

GP's decision process, nor the implications for the patient – and some considerable frustration!

The possible impact of missing information on patient outcomes was one significant difference

between the hospital and community settings. The community-based patient was often quite

well; and it was less likely there would be situations where missing information had an acute

effect on treatment – if there was a major problem the patient would be admitted to hospital.

Medication reviews in hospital were concerned with achieving control in acute situations,

whereas many of the community-based HMR issues (such as pain management, constipation

or incontinence) were ongoing. Nevertheless, although infrequent, community-based cases

did exist where acute issues (e.g. an adverse reaction to a medication) needed to be

addressed.

The main patient care goals for HMR pharmacists were: compliance with medications; patient

education; and optimising outcomes – the first two influencing the latter. However, as it was

often difficult to fully comprehend the situation – many pharmacists were unaware of patient

outcomes – it was generally assumed that the GP was managing the situation and that

Missing information meant that the HMR could be a ‘a bit of a pointless exercise’

However, there was ‘no point in chasing things up too much’; and patients were often considered to be ‘OK’ if nothing eventuated

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acceptable patient outcomes would eventuate.

In summary, as in hospital scenario, missing information was a significant problem for

accredited pharmacists in the HMR scenario. This problem was made more critical by the

pharmacist's dependence on the GP for patient-related information, although it was the

usefulness of the HMR report which was the main casualty – patient impact was less likely.

From the design perspective, the extent of missing information reinforced the researcher’s

belief that the digital document could not mandate the inclusion of information elements, only

suggest them and support their inclusion – aiming to collect missing information elements

where possible during the HMR loop.

6. 3.2 Information granularityThe issue of information granularity did not explicitly arise per se during this scenario,

although, as the researcher noted the information sources described by the HMR pharmacists,

the viewpoint formed during the hospital scenario was confirmed.

The main source of patient information, the HMR referral from the GP, was usually received in

the form of paper printouts from Medical Director® Version 2 (MD)1. These were accompanied

by a referral letter containing the patient’s consent and other administrative information

requirements for Medicare payment. An examination of relevant printouts available from MD

revealed a variety of levels of detail in the information provided, including:

• ‘full summary’ (containing patient details, family history, social history, current

medications, immunisations and past medical history)

• ‘full patient history’

• ‘limited patient history’ (containing patient details and past medical history); and

• ‘medication summary’ (containing patient details and current medications).

Other information sources used by HMR pharmacists primarily were drug information

resources, either textbooks or resources in electronic format on laptop computers. Drug

information centres and on-line resources were also mentioned by pharmacists.

Thus, although the issue of granularity did not explicitly arise, the nature of the information

elements used by HMR pharmacists was similar to those used by their hospital colleagues.

1. MD is the most common GP desktop system in Australia, where it is reportedly used by over 16,000 GPs (http://www.hcn.net.au/md3/stoppress.asp, viewed 2006-09-21).

Although patients could ‘miss out on something’, it was difficult for the pharmacists to know what this could be

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This confirmed to the researcher that the elements in the information model would have to be

provided at different levels of granularity to support the pharmacists’ natural work process.

6. 3.3 Conversation and communicationMost communication for pharmacists undertaking HMRs occurred with the GP through the

written report. Generally, there was little verbal communication and few pharmacists contacted

GPs before medication reviews – aided by the fact that most missing information was non-

urgent. However, good pharmacist-GP relationships were highly valued by pharmacists.

Where there was the possibility of multidisciplinary meetings (e.g. in the country or in hospital-

community interface programmes), communication with GPs was reported to be better. The

ACF environment provided much greater potential for communication for pharmacists, not only

with the nursing staff, but also with visiting GPs – ACFs essentially mimicked a hospital setting.

The researcher observed that relationships between pharmacists and GPs could be the basis

for some unease. There were some qualms about questioning the GP, as some were

considered ‘tricky’ – although this depended on the pharmacist’s acquaintance with the GP.

Part-time pharmacists also saw themselves as being at a disadvantage when it came to

communicating with GPs as they would have less familiarity.

Good communication always existed for pharmacists – verbally or by other means – with other

community pharmacists. Meetings for continuing education and peer review were also

mentioned by pharmacists within the context of relationships, as they were valued

opportunities for exchange with peers.

In summary, conversation with other health professionals was essentially limited to the GP but,

even when information was missing, this communication occurred only infrequently. This

behaviour was, in part, based on the pharmacists' beliefs about GPs' attitudes to HMRs; and

the fact that patient harm would be an unlikely result of missing information made the problem

less pressing.

Nonetheless, less than optimal levels of communication between GPs and pharmacists in the

community setting places a heavy reliance on the referral information to provide all the

necessary information for HMRs – which does not occur.

6. 3.4 Time constraints and summary informationAlthough the researcher did not observe time constraints as an issue for pharmacists

themselves (as this scenario was concerned with benchtop testing), respondents did raise time

Pharmacists could walk ‘a fine line between getting the message across and offending the doctor’.

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as an issue for GPs in dealing with HMR reports (and probably for initiating referrals, given the

poor quality many pharmacists noted). As pharmacists aimed for concise, summarised reports

to minimise the time impact (and maximise report impact) on GPs, the notion of summary

information as an efficient means of transfer seemed to be reaffirmed to the researcher.

In the hospital, an information summary was seen as a possible way to alleviate the need for

pharmacists and MOs to assimilate multiple information sources to gain a concise impression

of the patient. The information summary in the community context offers the same opportunity

– a concise and efficient impression of the patient after a medication review.

6. 3.5 Decision support tools

6. 3.5.1 Decision support tools used by pharmacistsThe use of decision support tools by HMR pharmacists was limited primarily to some on-line

and some computer-based drug information databases (i.e. of the simple NEDST Type 1

described in Chapter 2). Two pharmacists used Microsoft Access®-based databases which

had been developed to support RMMRs (but found useful for HMRs). Pharmacists found these

databases advantageous because they helped with report writing, although they could also

help the pharmacist undertake drug usage evaluations for ACFs. One database (Mediflags®)

incorporated a range of clinical information templates which could be used to formulate reports

for GPs. However, most pharmacists used Microsoft Word® (templates) for writing HMR

reports.

One pharmacist had substantially more information technology (IT) experience than the

others, having used MD (for reports), a ‘sticky notes’ application on a shared network and a

peer support network. This pharmacist also mentioned occasionally using a Palm application

for the 'easier ones' (i.e. HMRs) – although little detail was provided about this to the

researcher.

Drug information support for pharmacists came from a range of texts; and some on-line

resources. One pharmacist used the AACP website to access general treatment guidelines

and to pose on-line questions to other HMR pharmacists, especially about the use of CMs –

patients were frequent users of CMs at home and such information was often not available in

standard texts.

6. 3.5.2 Pharmacists’ understanding of decision support

As with their hospital colleagues, the understanding of decision support reflected the

pharmacists’ experience and no distinctions were made between the computer, telephone or

paper-based decision support. Pharmacists who were more IT-experienced offered views

such as: a ‘program that helps or guides to make better informed decisions, alongside use of
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knowledge’ – as with the hospital scenario, this suggested a tool to complement personal

knowledge.

Some of the paper-based decision support tools mentioned by pharmacists included

algorithms or clinical pathways (e.g. for cardiac failure or myocardial infarction) – these were

seen to encapsulate knowledge and eliminate the need for the pharmacist to seek further

information. The telephone-based support services mentioned by pharmacists included: the

Drugs and Therapeutics Information Service; and the Therapeutic Advice and Information

Service – ‘I ask a question and they give me an answer’.

6. 3.5.3 Fitting decision support into work practicePharmacists’ suggestions were about how decision support could be physically delivered, e.g.

notebook computer, PDA, telephones, on-line – or ‘electronic’ as a general term. However, the

researcher thought that an interesting aspect of these responses was the sense of where

decision support was expected to fit within the HMR process. A decision support tool was

unlikely to be used during an interview (other than perhaps if PDA-based, although again no

detail was offered as to how this could be done) as this was not convenient and pharmacists

wanted to concentrate on the patients themselves. The use of tools was more likely to occur

before an interview (e.g. to familiarise oneself with a disease), or after the interview (e.g. to

check about patient adverse effects). Pharmacists expressed a preference for use of a tool

after the interviews. This preference was based on the fact that, as information (about

medications and issues) on the referral was often incorrect, the referral information would not

reflect what was happening to the patient at home – this information would be more complete

after the pharmacist’s interview with the patient.

6. 3.5.4 Is decision support a realistic expectation?There was a general absence of opinion about this question. Pharmacists who were aware of,

or were using, tools (such as Mediflags®) thought decision support was realistic, but this was

based this on improvements in functionality of those tools. However, most pharmacists were

uncertain about how realistic decision support really was – although this uncertainty could also

stem from their general inexperience with technology.

6. 3.5.5 An ideal decision support tool

As with hospital participants, the expectations of HMR pharmacists about ideal decision

support tools reflected their personal experience. For example, the pharmacist who used

clinical pathways and guidelines mentioned these again at this point; and the pharmacist who

mentioned the use of drug information services also mentioned these once more. Expectations

Decision support was generally considered to be anything that helped professionals with decision-making

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tended to relate to content, rather than functionality – ideal decision support tools should be

based on up-to-date, evidence-based resources which consolidated information. Where types

of information were explicitly mentioned by pharmacists, these included: laboratory results;

diseases and, of course, medications (including drug interactions).

Of interest to the researcher was that pharmacists mainly mentioned drug-related or disease-

related information (i.e. reference information), but there was little reference to systems of

support for patient-related information – the area of greatest need. It is possible the reason for

this information 'bias' may be similar to that concerning pharmacists' perception of what a

decision support tool is – as pharmacists have not experienced a decision support system

which provides patient-related information, perhaps they cannot conceive of one.

‘Electronic sources’, however, were considered by pharmacists to be a more convenient way

to maintain information than paper-based sources; and electronic guidelines were considered

especially useful.

In summary, HMR pharmacists' day-to-day experience of decision support tools was far more

limited than that of their hospital colleagues. Because this HMR group was far less

sophisticated in technology use, there were also fewer clues available to the researcher about

technology needs. The main finding was an insight as to where a decision support tool might

fit within the HMR process – before or after the actual patient interview.

6. 3.6 Systems for experts rather than expert systemsPersonal knowledge emerged as a prominent issue for HMR pharmacists, just as it did for their

hospital colleagues.

HMR pharmacists' practical experience played a significant role in their knowledge acquisition

– e.g. acquired knowledge of common adverse effects in patients in particular situations

became the basis for caution in approaching new situations – to avoid repeating actions which

had previously led to errors or adverse events for the patient. In lieu of evidence, pharmacists

often used empirical judgement based on what had/had not worked in the past, to make

decisions about medication. However, one pharmacist issued a note of caution, stating that

that the more they knew, the more they realised they didn't know. This is a typical expert

judgement, and tends to confirm the expert status of the HMR pharmacists who participated in

a ‘quick screen’ to check for interactions or explain symptoms

(you are) ‘constantly thinking on your feet’

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the study.

In the same way that clinical pharmacists in hospitals evolve into 'specialists', so too do HMR

pharmacists evolve within the community setting. This is evidenced prima facie by the

requirement to undertake further training for accreditation. But in the presence of less

information (compared to the hospital), the reliance on use of personal knowledge was very

great. With even greater difficulty in capturing all the information for effective HMR reviews, it

seems highly appropriate to provide all the essential information needed to complement the

use of the pharmacist's personal knowledge. This finding helped to influence the design of the

prototype tool for the community environment.

6. 3.7 A technology-poor practice paradigmAlthough it was possible to for the researcher to establish the workflow process and technology

use by HMR pharmacists from the general questions in the interviews, the researcher felt an

additional, directed set of questions would provide richer data about these aspects which could

have implications for how the digital prototype might be used or should be implemented. A

summary of findings is shown in Table 6-6.

The paucity of technology use in the HMR environment throws up a paradox. Pharmacists

have used (computerised) dispensing systems for many years and many have experience of

Table 6-6: Workflow and technology use in the HMR process

Work flow item Information processing & transfer and technology used

How is the HMR request is received?

Notification to the pharmacist of the HMR was through the patient’s preferred pharmacy (unless they worked at the pharmacy and would therefore have the referral direct from the GP).The main delivery methods for referrals were by fax or mail. Where referral notification was by phone, the pharmacists would collect the referral from the GP practice in person. Two pharmacists mentioned the possibility of receipt by email (although this did not occur).

How HMR is the request processed (including any information transfer)?

There was generally little pre-processing of the referral before the medication review. Two pharmacists mentioned they pre-populated the HMR report with MS Word. Referrals were often 'screened' with the aim of browsing the medications, or for unfamiliar patient conditions.

What is the process for conducting HMR?

All pharmacists used hand-written notes on the paper copy referral (or partial report) at the time of patient interview. No pharmacist used a notebook computer during the interview.

What is the process for report writing?

Reports were prepared with a word processor (using Microsoft Word® templates), This often was in the form of a report that summarised patient issues and medication use. One pharmacist reported by exception using a ‘letter style’. Two pharmacists used a database for reporting.

What is the process for the delivery of report to the GP?

Fax, and then mail were the most common forms of HMR report delivery. One pharmacist faxed directly from a notebook computer. Delivery could also occur in person depending on proximity to the GP practice. Email was mentioned as an option for delivery of reports to pharmacies, but this seemed to be hampered by privacy concerns for a few pharmacists.

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computer-based information tools – they could be seen by others as quite ‘experienced’ in the

use of IT. However, the shortage of tools to support medication management (described in

Chapter 1), has been confirmed by the researcher in this scenario. All pharmacists were using

‘simple’ technology support, e.g. mainly word processing tools for HMR reporting. There was

very little (if any) use of technology-based communication tools, e.g. email or web-based tools

– the use of paper-based information sources prevailed. In light of these observations, perhaps

they should be considered ‘application-literate’ rather than ‘computer-literate’ (as would be

many health professionals).

Nevertheless, the pharmacists were certainly not adverse to trialling the digital document –

there was little effort required for the researcher to convince them to be involved in the project.

The researcher gained the impression that simple, useful tools to help with HMRs would be

welcomed.

There are two main implications of this ‘technology-poor practice paradigm’. Firstly, there is a

need for some technology to better support the communication of HMR information (this could

be as simple encrypted email); and secondly, a paradigm shift is required, from paper-based

to technology-based pharmacy practice in the community.

As mentioned earlier in this Chapter, two additional themes emerged from this phase of the

empirical research, which were specific to the community environment: the viewpoints of

professional practice tools; and pharmacists' perceptions of GPs in the HMR process. The next

two sub-sections of this chapter discuss these themes.

6. 3.8 The ‘viewpoints’ of professional practice toolsSome pharmacists held the view that the digital document should 'mesh' with a GP's desktop

system – and possibly even incorporate some features of (traditional) prescribing and

dispensing systems. This suggestion, however, would have led to a complete change in the

software solution being investigated and proposed in this thesis. There is no intention to

duplicate features of GPs' existing desktop systems, since they serve quite different purposes

to the medication management solution which forms the focus of this project. The researcher

considers these traditional systems have particular worldviews, or 'viewpoints'.

The function of a prescribing system is to allow selection of medication from a Pharmaceutical

Benefits Schedule (PBS)1 list – supported by features such as drug-drug interaction, some

drug-disease interaction checking etc. A dispensing system also allows selection of a

1. The Pharmaceutical Benefits Scheme subsidises payments for a high proportion of prescription medi-cations bought from pharmacies

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medication from a PBS list, with associated drug-drug interaction checking against the patients

prior supply record. Both these systems are built around supply of items to the patient from a

(common) list of medications: prescribing is concerned with the intention to supply (to the

patient); and dispensing with the actual supply of the medication. Neither, however, can lay

claim to actually representing what the patient is actually taking (although this can be the belief

of some GPs and pharmacists).

In relation to broader medication use, the prescribing system (MD) can record CM and OTC

medication taken by the patient (if this is volunteered by the patient) and if this medication is

included within MD. A dispensing system does not capture any such CM or OTC use.

The only way to reveal actual medication use is by means of a medication review; and the

purpose of the digital document investigated and prototyped in this research project is to

support that process. The digital document could truly represent the 'current medication record'

of an individual patient. It could only do so effectively, of course, if it is made available to both

patients and their relevant health care team on an ongoing basis – and, of course, no matter

how effective the solution proposed in this thesis, such an outcome can only be achieved if

both the GP and pharmacist are actively engaged with their patients in managing medication.

Nonetheless, a digital document living in its own ' electronic space' offers an opportunity to

provide a complete picture of a patient's medication use and compliance, whereas the

traditional systems are unable to do this. Prescribing a medication will not ensure it is

dispensed; and dispensing a medication will not ensure it is taken by the patient – neither can

represent actual use.

In this researcher's opinion, the desired ideal of integrating a current medication record

information (as advocated by the digital document) with existing prescribing and describing

systems is unlikely, because of the differing 'viewpoints' of the system types.

6. 3.9 Pharmacists’ perceptions of GPs in the HMR processAs reported earlier, communication between pharmacists and GPs was infrequent; and often

undertaken reluctantly. During this discussion, the researcher noted that pharmacists felt

some GPs were not convinced of the value of HMRs: a viewpoint reinforced by pharmacists'

experience of poor, or no, feedback from GPs. Not only is this situation unfortunate, it also has

implications for patient safety – pharmacists were often unaware of the outcomes of their

interventions. Pharmacists suggested that sharing the digital document on-line might not only

improve the information sharing process between these two groups – it might also contribute

to improving relationships between GPs and pharmacists.

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6. 3.10 Prototype testingPrototype testing is reported as a separate discussion as this was the true 'test' of the

information model and digital document. The discussion in this section combines data from

feedback about the prototype solution from the focus group, directly based upon participants'

reporting of their satisfaction with use, or by means of the researcher's owner observations. As

with much of the other data, this section will summarise findings. More substantial and detailed

reporting of the testing process can be found in Appendix O.

Where possible, the researcher attempted to observe prototype testing by pharmacists first-

hand, to reveal aspects of use which might not be reported by participants, e.g. which digital

document page they used first. Of course, as participants were being observed, use may not

have been 'normal' (the Heisenberg Uncertainty Principle1). Unfortunately, it proved possible

to observe only two of the five pharmacist participants, so only limited impressions could be

formed by the researcher on the basis of his observations. These pharmacists nevertheless

reported their use at the focus group or in other communication, so that observation was not

the only method of obtaining feedback from the usage of the prototype.

The researcher's impression, overall, was that pharmacists had little difficulty in using the

digital document and rapidly gained speed in using it once they had some initial familiarity with

the prototype. Speed of use only decreased when pharmacists were deciding how to word or

apportion text into fields (e.g. whether to describe a paracetamol dose as 1g or 2 tablets; or

whether to include an instruction of 'prn for pain' or place the word 'pain' in the indication field).

There were often questions about the intent of fields or what do in the case of a missing item

– the researcher made no specific suggestions about what to do in these cases, as the

intention was to observe actions, rather than to direct use. Observations also provided an

opportunity for the researcher to determine other needs (e.g. confirmation dialogue after some

actions, the need to resize or reformat screen components, etc.), or to note errors for

subsequent correction.

The following subsections summarise the results of the prototype testing, using the headings

which were used in the data gathering document.

1. The Heisenberg Uncertainty Principle has its foundations in quantum physics but its conservative inter-pretation is that uncertainty is a limitation imposed by our measuring techniques (http://plato.stan-ford.edu/entries/qt-uncertainty/#HeiRoaUncRel; viewed 2007-02-27).

Some pharmacists felt that the GP was ‘just following a (mechanical) process’

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6. 3.10.1 User reactions to the prototypePharmacists generally had positive reactions to the prototype and thought the concept was

good.

It was considered easy to use, although entering data was generally was found to be more time

consuming than pharmacists’ existing methods of entering data (using Word® templates), as

more information was requested by the digital document than was currently recorded for a

medication review (e.g. the start date for medication) – although one pharmacist declared that

‘it's about what you get used to’.

6. 3.10.2 User suggestions for the prototypeNot surprisingly, participants had many comments about the information elements or structure

of the document – this was expected, as not only was this the first test of functionally, but

testing was also intended to identify those elements required for the community context. A few

issues in particular were the basis of much discussion.

Opinion about the use of drop-down boxes was varied – some pharmacists considered these

useful (to save typing and time), while others preferred text boxes (to save searching through

long, e.g. medication lists, and time). This conflicting requirement is a good example of the

dilemma which can exist in satisfying user needs during development. In any case, the

researcher decided that (large) drop-down lists were not in keeping with the digital document’s

aim of being of a transportable and shareable medication-related record.

Pharmacists expressed some support for alerts and reminders during prototype testing, but the

consensus of the focus group was that these were not generally important. Using the examples

of weight and height, there would be only a small number of patients where such information

was considered important. Changes in weight were considered more important that an isolated

value of weight per se. The researcher considered this to be an interesting comment in light of

the poor information conveyed by GPs – they would probably be more likely to provide a weight

value than a more detailed comment about changes in weight.

Despite their overall advice that reminders were not critical for the system, pharmacists did

consider some alerts to be useful, including: a flag for any recent biochemistry; a more specific

flag for a recent INR; and a date indicating when the medication list had last been updated. In

the same thread of discussion, pharmacists considered that calculators for Body Mass Index

(BMI) and creatinine clearance (a measure of renal function) were useful, as many

pharmacists used these tools regularly. Some of the more important suggestions for changes

Generally (it) 'asked the right questions’; and was ‘logical with the right layout in the right order’

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to the digital document are shown in Table 6-7.

6. 3.10.3 User innovationsPharmacists also suggested many new features for the digital document. Many suggestions

were good ones, but a number would be difficult to implement or represented a direction

contrary to that of the digital document. Other suggestions were made by an individual

pharmacist, but were not representative of the group. The main issue for the researcher here

was not to succumb to the general trap of requirements elicitation, but rather to maintain the

goal of recognising essential information elements and appropriate digital document

functionality. Consequently, not all the ideas suggested were used to make changes to the

information model or (functional changes) to the document prototype. Suggestions which

were, and were not, implemented are summarised in Table 6-8.

Table 6-7: Pharmacists’ suggestions for changes to the digital document prototype

Changes

The date of birth should be recorded rather than age (as the next time the document was opened the age would be the same value and possibly incorrect); and the ability to record ‘unknown’ or other text value for date, as this may not be known.

Use of separate generic and brand names for medications.

Changing the cursor shape when this moved over a link. This changed from arrow to a ‘line cursor’ that was difficult to see – a hand-shaped cursor was suggested.

Highlighting the selected item on a list rather than having a box around it, as this was difficult to see.

Have the route of administration default to ‘oral’ (possibly with some other limited choices).

The ability to use headings on a report e.g. actions carried out, education undertaken and items for discussion.

Table 6-8: User innovations

Implemented Not implemented

Addition of patient risk factors (e.g. for cognition, eyesight).

Ability to print out a medication list for the patient.

Recording indications for medications from the patients’ perspectives.

Ability to record patient concerns.

A place to record social issues. Ability to use keyboard shortcuts as well as the mouse (Unable to do within project timeframe).

Capture medical / treatment history / inactive problems

Addition of yes/no confirmation when deleting entries (unable to do).

Tick box for common immunisations. An action plan (for the report).

Reason for referral field with an ability to add further comments (to be the basis of the report).

Ability to flag or highlight results and / or items indicating what was different in the report compared to the referral.

Separate lists for ‘regular’ and ‘when required’ (prn) medications.

Comments’ field after the medication information.

Add contact details for others (e.g. carers) Ability to print out a list of patients who underwent an HMR

Headings for information to share with the GP: issue (raised by GP), suggestion (by pharmacist after review), outcome (after the GP considers pharmacist recommendations).

‘Tick boxes' against issues to flag if they were resolved; and the same for the patient overall.

Ability to group drugs in the medication list.

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The term 'compliance' (as a text box label on the digital document) was considered

inappropriate – compliance was considered to be part of general management issues and it

was felt that a better approach would be to use the label 'medication management' with some

examples in brackets (e.g. compliance, handling, understanding). The recording of 'social

issues' was important to pharmacists, as many GPs were unaware of how these issues could

help the pharmacist undertake the HMR.

The ability to signal particular concerns about the patient, e.g. visual impairment, cognitive

problems etc. was deemed important, as these were patient aspects that could either affect

medication management or, in turn, be affected by the medication. One important addition was

the ability to indicate a recent fall – not featured on currently used referral documents.

One suggestion was to not include a feature: participants felt that a tick box listing the HIC

medication risk factors should not be provided within the document, believing that a text box

to enter the (real) reason for referral would provide more useful and actionable information.

6. 3.10.4 Functional prototype issues One area of significant discussion was dates, as all pharmacists experienced problems with

the way dates were handled within the prototype. The date field was displayed in an unfamiliar

format (yyyy-mm-dd) and entering an invalid date value prevented the document being saved.

Participants also discussed the more general issue of when dates should be used – believing

this to be important in certain cases e.g. when indicating a current course of medications, or

when weight or height were recorded. Such use would therefore depend on the particular

patient circumstances. The use of a default date value (of 'today') was seen as problematic, as

this could encourage users to take the easy option of leaving this value – which could give rise

to misinformation. This issue with unchallenged default date values often occurred with

referrals received from MD (i.e. they were wrong), but getting GPs to enter the correct dates

was considered 'a bit of a challenge'. It was felt that when there was no date to enter, values

such as 'unknown' or 'na' might be better options than a default date.

The medication and diagnosis lists were found to be cumbersome as a user needed to ‘flip’

back and forth between the display page of the document and the relevant data entry form

(these were the longest lists of items for any HMR document). A proposed solution was a

‘blank’ record for subsequent entries (similar to a database). The order of medication items

was also an issue as new items were inserted on the top of the medication list. A preference

emerged for the ability to group ‘important’ drugs (e.g. warfarin, anti-hypertensives, or drug

classes) at the top of the list; and to place the less important ones (e.g. laxatives) at the bottom.

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Further discussion arose over the labels of ‘diagnosis’ and ‘active problems’ as these reflected

hospital (discharge) and were confusing in an HMR context. As well, discussion revealed that

patient concerns and GP concerns might differ – a patient concern might not be a GP concern

and vice-versa – there was thus a need to record patient concerns (to feed back to the GP).

In summary, the main usability findings from prototype testing concerned issues associated

with date functionality, previously unnoticed errors in display; and changes required in the

underlying data structures based on the different context. Document analysis, which again

contributed to knowledge about information element frequency, is discussed next in Sub-

section 6.3.11.

6. 3.11 Document analysisDocument analysis was a simpler process for the researcher compared with the hospital

scenario, as the benchtop scenario had fewer participants, but also because there was a

smaller range of documents. Consequently, there was no need for the researcher to construct

a UML model (as with hospital-based documents). The documents used by this group

essentially were a referral from the GP, or report sent to the GP – these are discussed in the

next two sub-sections.

6. 3.11.1 Referral documentsThe referral documentation from the GP generally consisted of a referral letter accompanied

by one of a range of reports from MD. As the researcher was only able to obtain a small sample

of these documents from a comparatively few pharmacists, other representative sources of

HMR referral documents were sought. These included sample printouts from MD; and

documents published by the National Prescribing Service, Mediflags®, the Pharmacy Guild of

Australia and the Port Macquarie Division of GPs. As with the hospital scenario, the document

analysis was not intended to be either an extensive audit which would capture every single

information component that could be included in referral documents – rather, the components

that were most commonly represented. The researcher then analysed the information

elements contained in these documents and compared them with information elements of

models that he had formulated for the hospital scenario (for missing medication, patient

information and document analysis). These comparisons determined which information

components were common to both scenarios (confirming the importance of that information

component); and those which were needed to represent the community context – the latter

becoming candidates for inclusion into the information model. These comparisons confirmed

the need for the information elements identified for the hospital scenario, as well as suggesting

further community-related information elements. The spreadsheet contained in Appendix W

shows these comparisons in full.

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6. 3.11.2 ReportsThe HMR reports created by the pharmacists were invariably simple – some reports were

designed to be no longer than a single page. This brief report contained a concise summary of

the investigation of the issues raised by the GP (if any), any issues identified during the review;

and any subsequent recommendations for action. The reports from different pharmacists were

very similar as the Microsoft Word® templates used as the basis of the reports were often

shared through the HMR pharmacist 'network'. Some reports were based on Mediflags®

templates. The information components contained in a typical report included: patient details,

GP and pharmacist contact details, date of interview, patient diagnoses, social issues, (patient)

equipment used, concerns about the patient, allergies and Adverse Drug Reactions (ADRs),

current medication including indications, potential drug related problems/interactions, actions

taken by the pharmacist; and issues for consideration by the GP.

6. 3.12 Opportunities for the digital document to improve HMR practice

6. 3.12.1 The medication management review processPharmacists' opinions about ways in which the digital document could help the medication

management process, or improve patient outcomes, were of considerable importance to the

project – as well as to the researcher. In this, however, as with some of their suggestions for

new features for the prototype, pharmacists recommended features which were too broad to

be accommodated within this project. Nonetheless, these suggestions did serve to place the

digital document in a wider context than simply capturing HMR information.

Opportunities were seen to use the digital document to:

• complete the information loop between the pharmacist and GP. Participants suggested

that this would: enable the GP to acknowledging receipt of HMR information more

quickly and to send comments back to the pharmacist; increase GP accountability; and

potentially improve GP-pharmacist relationships. Such an approach might address the

problem of pharmacists not receiving medication action plans back from the GP, or

receiving feedback only after a further event occurs for that patient (e.g. going back to

hospital)

• streamline the HMR process for pharmacists, e.g. decrease the amount of typing

required after receiving the referral and, in particular, use the digital document as the

basis of an HMR report

(the current process was) ‘see the patient, write the report, send it to the doctor and eventually they get it, and think about it some time in the next few weeks’

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• enable the use of small, hand-held devices for data capture during patient visits, to avoid

having to later re-type information into a computer

• provide the basis for progressive plans as the patient moved through a number of HMRs,

hospital admissions, etc.

• standardise the format for HMR reporting

• form an audit tool for pharmacists (to review HMR practice)

• allow printing of material for patients (such as a medication list).

6. 3.12.2 Opportunities to improve the patient outcomesAlthough participants mentioned improving patient outcomes as a general benefit, they were

less specific on this topic than when discussing opportunities to improve the HMR process.

One improvement suggested in relation to improving patient outcomes was the idea of using

the digital document has an information tool – 'the more information the better' – although this

was disputed by other participants, because the act of recording more information does not, in

and of itself, improve patient outcomes. Improved outcomes were seen to be more associated

with the ability to improve communication (about the patient) between the health care team,

the patient and the family.

The timeliness of information, in particular, could affect patient outcomes. For example, during

a hospital ward round, a recommendation from a pharmacist could be enacted immediately,

so that the patient benefited immediately. With an HMR report, however, it was never known

if pharmacists' recommendations were put into action. If the information loop was completed,

therefore, important messages requiring immediate attention could be flagged to the GP, to the

benefit of the patient.

In summary, analysis of the data gathered from interviews, prototype testing, document

analysis; and the focus group provided the basis for amending the hospital-based information

model for HMR use in the community. Prototype testing also assessed visual and functional

components of the digital document in preparation for field testing. The community-aligned

model is discussed in Section 6.4; and changes to the digital document and other

implementation details in Section 6.5.

6.4 The community aligned information modelThe researcher's approach to refining the information model has been mentioned in some of

the previous sections of this thesis – not all elements or ideas suggested by HMR pharmacists

were adopted. Those which were adopted supported the project's goal of realising a portable

and flexible digital document to support medication management. This necessarily meant

avoiding complexity within the document which would not only divert the project from its
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intention, but also add issues of system size and performance. Some problems could not be

fully resolved satisfactorily, e.g. the date format problem, but had to be left for future work.

The major changes to the information model are shown in Table 6-9.

The revised information model is shown in Figure 6-2. This figure also shows the changes

made to the hospital model once the community material had been incorporated. Information

elements marked with a double asterisk (**) are new items added to the model; a single

asterisk (*) indicates that an item existing in the hospital model was amended in the community

model; and items marked with an ampersand (&) have been removed from the model. The

revised model included two calculators (##): one for Body Mass Index (BMI) and one for

creatinine clearance; as well as two alert functions (!!): one for the detection of warfarin in the

medication list and another which looks for warfarin and the presence of an INR in the

laboratory investigations list.

The implementation aspects of the model and other functional changes implemented in the

document are described in Section 6.5, with full details contained in Appendix P

Table 6-9: Information elements added to the model for the community context

Information group Information element Change from hospital to community context

Referral information All elements. This information was not required in the hospital.

Patient information Calculators for body mass index and creatinine clearance.

These would be available by in other ways in the hospital setting.

Recent BP (blood pressure). Available in other sources for hospital pharmacists.

Serum creatinine. Required by the calculator.

Other contacts. For family members, other health professionals in the community.

Physical information group. Factors that can affect adherence to medication for patients in the community (or can be affected by medication e.g. falls).

Medication information Immunisations group. An important consideration for the elderly in the community.

Generic and brand names. This existed as a single element in the hospital Mode, where the generic name is preferred.

Regular and when required medications.

This existed as a single group within the hospital model.

Alert for presence of warfarin. Added to test usefulness of alerts in the community setting.

Investigations group Alerts for presence of INR (and along with warfarin).

Added to test usefulness of alerts in the community setting.

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Figure 6-2: The community-aligned information model

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Page 198

6.5 The digital document and the server serviceThis section describes the changes made to the Visual Basic (VB) viewer and the XForms

document, as a result of the bench top testing, together with the development of the server

service to support on-line access. Screen dumps in this chapter are only used to illustrate

major changes, rather than being used in all cases – sometimes only a small section of the

screen is shown (the area of interest), as a compromise between clarity and the use of space.

6. 5.1 The VB BrowserThere were minimal changes to the existing VB browser other than some minor formatting to

allow better sizing of the form for a lower resolution screen on a PC or notebook; and

maximising the display area for the digital document within the form.

However, the need to print a paper copy of the digital document required the researcher to

develop a new VB form. This ‘child’ form (VB Document Printer form) was launched from a new

[Print] button added at the top right of the VB form – shown in Figure 6-3.

The code contained within the VB Document Printer form used an XSL1stylesheet to transform

the patient’s XML file into an HTML format for display in the form’s window (for subsequent

printing). This child form option was faster and ‘cleaner’ than producing an HTML report in the

existing VB viewer, which would have required: saving the current document; producing the

HTML report; and then possibly re-opening the document again after printing. As opening the

document was a relatively slow process – the entire XForms document needed to be parsed

– avoiding this was clearly a better option. The source code for this second version of the VB

viewer is contained in Appendix R.

The VB Medication Management Document Printer form is shown in Figure 6-4 (on top of the

calling form).

1. eXtensible Stylesheet Language (XSL) stylesheets are designed to format output from XML docu-ments.

Figure 6-3: Visual Basic document viewer (version 2)

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The researcher designed the function of the buttons on the VB Document Printer form to be

similar to those on the calling form to the greatest extent possible. For example, the [View

patient documents] on the main form and [View existing patients] both opened a list of existing

patient documents. The button functions are explained in detail in Appendix P.

Figure 6-4: VB Medication Management Document Printer form

Page 200

A sample of a HTML report is shown in Figure 6-5. Clicking on [Send to printer] subsequently

opened a Microsoft Windows® printer dialogue box. The XSL code that causes the

transformation of the XML file to HTML output is contained in Appendix V.

The changes to the digital document pages required by the findings of the benchtop testing

phase of the project are now described, beginning in Section 6.5.2.

6. 5.2 The digital document Referral details page

The referral details page (shown in Figure 6-6) is new to the model; and is an obvious

consequence of the community context findings. The page contains the referral date, reasons

for referral (entered ideally by the GP) and the review date subsequently entered by the

pharmacist. The date values at this point are simply text values as there is no need for date

calculations on this page.

Figure 6-5: VB HTML output of the digital document

Page 201

.

This page also illustrates the ability of the document to exhibit ‘dynamic behaviour’ based on

the context of use. The different GP and pharmacist use contexts have been distinguished by

the use of different information elements depending on who is using the document. At the point

of the referral, when the referral page is being used by the GP, this page looks like the example


After the review, when the pharmacist enters the review date, additional information elements

in the page are revealed – the report date and the completed date. The headings for the

referral output box are now different as well. In addition to the reasons for referral, display

elements can include:

• recommendations (entered by the pharmacist)

• actions (to be entered by the GP after considering the report) and;

• resolution/date.

The example presented in Figure 6-7 shows these additional information elements displayed

in the page.

Figure 6-6: Referral details page

Page 202

The same principle is used in editing reasons for referral where at the time of referral, reasons

for the referral can be added through use of a simple text entry form that appears once ‘new

item’ is clicked – shown in Figure 6-8.

The user's ability to add multiple referral entries using [Save and add another] was also added

to the documents functionality. This approach was also repeated for other potentially long lists

– such as medications and active problems.

In keeping with context awareness, once the HMR review date was entered, the form in Figure

6-8 changed to also reveal fields for the additional information elements, shown in Figure 6-9.

Figure 6-7: Referral details page – after the review

Figure 6-8: New reason for referral form

Page 203

These additional fields allow the pharmacist to add a recommendation alongside the referral

reason; and the GP to later add an action for the pharmacist’s recommendation. This

interchange between the pharmacist and the GP forms the basis of a potential action plan. The

resolved/date fields can be used by the pharmacist or GP if they consider the referral reason

is resolved.

6. 5.2.1 Patient details pageThe changes to the patient details page are shown in Figure 6-10. Differences from the

original page are: the display of calculated values of BMI and creatinine clearance, day values

(shown in blue) are now calculated as month values, the red Omega alert is now a * symbol;

and there are tick boxes to record patient concerns (cognition, memory etc.). Text areas were

also added for Other problems and Equipment used – both of these fields open to reveal

simple text editing forms. In the case of patient falls, ticking that option opens two fields to enter

additional information (fall details and date) – this is important as falls predispose the patient

to further falls (with a high mortality rate); and the circumstances of the falls can be particularly

important.

Figure 6-9: Extended reasons for referral form

Page 204

Figure 6-10: Patient details page

Page 205

The expanded fall section of the document is shown in Figure 6-11. All other functions on the

patient details page were unchanged from the hospital document.

6. 5.2.2 Treatment details pageThis page is not shown in this chapter as the only changes were the re-labelling of the

information groups: Principal diagnosis to Active problems; and Past medical history to

Medical history.

Figure 6-11: New reason for referral form – falls

Page 206

6. 5.2.3 Medication pageThe medication page (Figure 6-12) underwent the most significant changes of any previously

existing page.

The first change was the addition of a section for immunisations which are commonly used for

elderly patients: including tetanus, influenza vaccine and pneumococcus vaccine; and an area

to record others. The edit form for these is shown in Figure 6-13.

Figure 6-12: Medication page

Page 207

The other significant change is the division of medication into two groups: regular medications;

and when-required medications. These have similar edit, new and delete functions and, as

before, there is the option to display medication history. This display of medication history also

needed amendment to accommodate the two different types of medication.

Current medication was shown as a combined block of the current regular and when-required

medications; and history was shown as two separate groups of regular and when-required

medication. An issue not initially considered on the hospital document was that the edit, new

and delete function options (triggers) were still visible when the medication history was

displayed. These were removed from the display, leaving only a 'hide medication history'

option. The medication history report is shown in Figure 6-14.

Figure 6-13: Edit immunisations form

Page 208

Figure 6-14: Medication history

Page 209

Another more subtle change to the current medication list was the ability to enter a patient

indication for medication after an HMR had been undertaken (i.e. why the patient thought they

were taking the medication). In the same way that entering the review date made additional

information fields visible on the referral page, it also allowed the Patient indication field to come

into view in the edit medication details form – indicated in Figure 6-15.

The value of this information element was that it could identify confusion or potential problems

in patients’ understanding of their medication; and therefore possible influences on

compliance.

6. 5.2.4 Investigations pageThe investigations page did not change as a result of the benchtop testing and so is not shown

in this chapter.

6. 5.2.5 Health Professional ContactsThe Health Professional contacts page was renamed Health and Other Contacts; and a third

category of contacts (Other) was added to include e.g. family contacts or (Royal) District

Nursing Service. There were also some other information elements added into the doctors and

pharmacy details – telephone, fax and email. The drop down list for doctors in the edit doctor

form was changed to GP and specialist, rather than attempting to specify a group of relevant

specialists as in the hospital document (this simple classification was preferred because

pharmacists suggested this was the way in which patients described doctors). As these were

minor changes, they are not shown in this chapter.

Figure 6-15: Edit medications form – after review

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6. 5.3 The server serviceAn important outcome of this scenario was the development of a server service to allow on-

line access. This was important, in keeping with the participants’ desires to able to

communicate medication-related information (i.e. the digital document). In this on-line

environment, the researcher aimed to duplicate, as closely as possible, the functions provided

by the VB viewer – the display of the digital document and the same patient file functions. In

addition, there was also a need to be able to upload and download patient files between the

server and a PC (or notebook computer). The ability to use the digital document on-line,

‘locally’ or as a combination of both, by transferring patient files between the server and local

computer, provided a great deal of flexibility so that the participants could accommodate their

work preferences (or try new methods).

The options available to users included:

• Using the document in isolation, i.e. for the pharmacist to use the patient documents on a

notebook or desktop using the VB browser-based approach (this would mean that the

pharmacist received a paper copy referral (mail or fax); and returned a paper copy report

to the GP).

• Using the document completely via the server. This offered the best option for efficient

sharing of the document. In this case, the GP referral would ‘change’ into the report after

the review information was entered by the pharmacist. (It was still likely that the

pharmacist would take a paper copy of the referral to the interview – no pharmacists

indicated that they used a notebook computer during interviews).

• Use a combination of both options, e.g. the patient referral could be created by the GP

on the server and later downloaded by the pharmacist, or the pharmacist could perform

the first part of the review process using paper and then load a completed referral report

onto the server for the GP to view. Other variations of this were possible.

The patient XML file could also be exchanged using encrypted email of course (as the average

patient XML file size was only in the order of 8–17Kb), although this option was not specifically

considered at this stage of the project. The different pathways for use of the document are

graphically summarised in Figure 6-16.

Although the server service supported exchange of the medication document, however, the

researcher did not attempt to accommodate the business aspects of the HMR process, i.e. the

referral letter required for HMR payment by HIC. This issue falls into the Future Work category

and is discussed in Chapter 8.

The researcher began developing the server environment using Apache Tomcat®, as this was

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a common approach within the University. But despite some initial success, this approach did

not allow the digital document to be delivered to users in its own browser ‘shell’ (like the VB

viewer). The researcher considered a number of approaches, including Java Server Pages,

Java Servlets and Java Swing. However, the learning curve for these was too steep for the

time frame remaining for the project and eventually the service was implemented using

Microsoft Internet Information Server® (IIS) version 5.1. A major advantage of this approach

was that Microsoft Active Server Pages® (ASP) used procedural code very similar to that used

for the VB viewer. An unfortunate disadvantage was that there was little (no) support for this

strategy within the University environment. Some of the development steps for the server

service appear in the development record are shown in Appendix Q.

A visual representation of the server service (detailing the relevant ASP files) is presented in

Figure 6-17. The code for all server pages is shown in Appendix S

Figure 6-16: Pathways for the HMR digital document

HMR documentDesktop PC

PC/notebook

Server

GP

Home Medicines Review

View HMR report

Enter HMR info

HMR report

EnterHMR

report info.

HMR info

Enter HMRinfo.

Enter review

info.HMR document

Pharmacist

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The different functions of the server service will now be described briefly, beginning with

security in subsection 6.5.3.1.

6. 5.3.1 SecuritySecurity was clearly important to ensure that patient data stored on the server was not

accessible to unauthorised individuals and could be communicated to users (GPs and

pharmacists) without risk. Server security was implemented using SSL with a self-signed SSL

certificate using Microsoft SelfSSL® version 1.0 (Microsoft SelfSSL.exe, http://

support.microsoft.com/kb/840671/#11). Microsoft suggested that this approach was suitable

when there was a requirement for a security-enhanced private channel between the server and

a limited, known group of users – suitable for the small number of participants in this project.

Server activity was also captured using a log.

Client security was achieved in two ways. Firstly, access at PC level (to the researcher’s PC

acting as the server) was used – following advice from University technical staff. The basis for

this approach was that since there were to be only a few participants, there would be no need

for a method of user self-enrolment – the researcher could enrol users and have complete

Figure 6-17: Server service for medication management document

login successful?

Patient exists?

mmrFunctions.asp

List patients Add patient Open patient Close document

patientList.asp

createNewPatient.asp

newPatient.asp

http:// … /MMR

getPatientFrames.asp

Frame: patientListframe(src=patientList.asp)

Frame: getPatientName(src=getPatientName.asp)

Non-displaying pages

mmrPrintGetPatient.asp

processForm.aspopenPatient.asp

Viewable pages

http:// … /MMR

noPatient.asp

mmr.asp

http:// … /location folder/patient files

choices.asp

Open viewer

Download document

Upload document

Print document

mmr_print.xslFolder/patient file

Default pagedefault.asp

getServerPatientName.asp

getLocalPatientName.asp

yes

no

Document viewer(mmrFrames.asp)

Frame: buttonFrame(src=mmrFunctions.asp)

Frame: displayFrame(default is src=blank.asp)

Frame: resultsFrame(src=blank.asp)

Local drive

Server

uphandler.asp(uses aspSmartUpload)

downhandler.asp(uses aspSmartUpload)

no

yes

Data transfer

Note: the target for all document displays is Frame: displayFrame contained in mmrFrames.asp

Note: the target for all document displays is Frame: displayFrame contained in mmrFrames.asp

mmrPrint.aspNEW WINDOW

LOGIN

Login errorlogin.asp

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control.

Secondly, a server service log-in further validated users; and pointed them to specific folders

where they had appropriate rights to create and manage their patient documents. The user

name and password were set by the researcher; and all security and privacy details were

discussed with participants. Further detail about security; and the log-in screens seen by the

users are contained in Appendix P.

Once users had successfully logged-in, they were presented with the browser view shown in

Figure 6-18, showing the options available to them.

The different ASP pages of the service are now described in the following subsections and, in

keeping with the intention of brevity used throughout this thesis, the fine detail, including

source code, is confined to appendices.

6. 5.3.2 Server pagesSelecting the [Open Document Viewer] option resulted in the display of the page shown in

Figure 6-19. This page was essentially the same as the VB browser form, showing function

buttons at the top to: list patients, add new patients; open patient files; and close the document.

The only difference between this and the VB browser was the document printing button

available on the VB viewer, which was located differently on the server service, i.e. on the very

Figure 6-18: Server options after log-in

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first page for the server (Figure 6-18) – and as a function button near [Close document] in the

VB browser.

The [List Patient files] function simply displayed a list of patients (appropriate for that user) in

the bottom frame of the page and the [Add New Patient] function provided a further page with

an input field to enter a new patient name (with subsequent confirmation when the new file was

created). These functions are described in Appendix P.

Figure 6-19: Document viewer with a ‘blank page’

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The [Open Patient File] function displayed the page shown in Figure 6-20.

The list of patients available to the user was shown in the left-hand frame so that users would

not need to remember what the patients they had in their list. Typing the name of the patient

in the input field and clicking on [Open document] would consequently display the appropriate

patient document in the bottom frame – shown in Figure-21.

Figure 6-20: Open patient document

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The [Close Document] function caused the document in the bottom frame to be replaced with

a ‘blank page’ to bring the user back to the view displayed in Figure 6-19. As with the VB

browser implementation, the document could be closed on the server without saving changes

that had been made to the information contained within it. Therefore the [Close Document]

option also displayed a confirmation message (using a simple VB Script message form) to

remind the user to save any changes to the document before proceeding.

Figure 6-21: The patient document displayed on the server

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By using the approach of ‘duplicating’ the features of the VB browser in the server

implementation, the researcher was able to provide a similar ‘look and feel’ in both

environments (as much as possible). Therefore, although some of the ‘surroundings’ of the

document would have to be different, the digital document itself would always be displayed in

the same familiar way for users.

The process of printing a paper copy of the digital document began with selecting the [Prepare

document for printing] choice on the Options page (Figure 6-18); and this displayed the page


Entering the patient name and clicking on [Get document] would call the ASP procedure to

cause the XSL transformation of the appropriate patient XML file and send the HTML output

to a new (IE) browser window instance. This window is shown, tiled over the calling window in

Figure 6-23.

Figure 6-22: Print patient document from the server

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The HTML report output could then be checked for accuracy by pharmacist and then printed

using the local Microsoft Windows® printing options available on the computer. The XSL

transformation process was a very quick and efficient way of generating a report and, since the

same XSL stylesheet was used for both the VB viewer and the server, the 'same' report would

be seen by users – ensuring further consistency.

To exchange patient files between the server and local PC/notebook, users could use the

[Retrieve document from the server] and [Send document to the server] functions on the

Options page. For these functions, the researcher used some public domain VBScript code –

Figure 6-23: HMR report output in new browser window

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smartASPUpload (http://aspzone.com/blogs/john/archive/2003/07/03/160.aspx) – which had

the advantage that, in addition to using a procedure which had already been tested, this also

saved considerable development and testing time. An example of [Retrieve document from the

server] is shown in Figure 6-24.

6. 5.3.3 Summary of the technical changesIn summary, the researcher did not implement all changes to the document suggested during

prototype testing, as some conflicted with the intention of providing a simple model containing

essential information elements. Other changes were outside the scope of the project and a

further group were too difficult to implement. To reiterate, as this project was a proof of concept

seeking indicative data about usefulness, implementation complexity was kept to a minimum,

rather than seeking to implement a fully featured system.

Figure 6-24: Save patient file locally

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A major undertaking for the researcher was to provide the ability to use the digital document

on-line, allowing an effective means of communicating the medication management document

between GPs and pharmacists. The combination of the server service and the ability to work

locally provided flexibility and allowed adaptation to GPs' or pharmacists' working styles – this

allowed the medication management document to be truly portable.

Only one potentially serious problem was experienced by the researcher during the

development of the server service – a sudden and debilitating failure in which the XForms

document could not display dynamic components (such as date objects). This was caused by

security patch updates for IE, provided by Microsoft. This problem is not detailed in this

chapter, but is mentioned by the researcher as a note of caution for those relying on widely

used applications (i.e. IE) to behave consistently.

6.6 Chapter summaryThis chapter reported the benchtop testing phase of this project, where the researcher took the

information model developed for the hospital context and assessed it for community use by

prototype testing by HMR pharmacists. The intent was to answer the research question:


The strategy used to answer this question was to investigate how medication-related

information was used by HMR pharmacists through the data triangulation of a combination of

questionnaires/interviews, work practice observations, document analysis, prototype testing

and a focus group.

Although the goals of HMR pharmacists for medication management and patient care were

similar to those of their hospital colleagues – medication optimisation and safety – this group

had a more holistic approach to patient care. Efforts were concentrated on ensuring patient

self-management, education; and improvement in the quality of life. In fact, the quality of life

for patients was often considered to be a more important issue than the management of

patients' medications or disease.

Some of the themes that arose in the hospital context were also relevant in this context.

Information use by pharmacists was characterised by a critical reliance on the GP – the result

was a great deal of missing information. The flexibility of the information model to cope with

this information lack was thus even more important. Notwithstanding the addition of the

necessary information elements for the community context, the good fit of existing information

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components to HMR pharmacists confirmed to the researcher that the information needed to

exist at different levels of granularity.

In contrast to the hospital situation, information seeking by conversation was rare in the

community context, increasing the importance of, and reliance upon information provided by

the referral document – a difficult dilemma. This also raised the issue of relationships with GPs

and how this affected the attitude towards information seeking behaviour.

Although time constraints did not emerge here for pharmacists, they perceived lack of time to

be important for GPs' ability to deal with the HMR report – and for any subsequent feedback

the pharmacist might receive. This issue supported the notion that an artefact with

summarised, relevant patient-related information which was appropriate for hospital use could

also be relevant here for use by the GP.

Against the background of the scarcity of appropriate information, the significant reliance on

personal knowledge by pharmacists during HMRs (and specific training for this role) suggested

that they were experts within their own context. This suggests that the hospital-based

approach of an essential information model to complement the use of personal knowledge is

also appropriate in this context.

As well as the lack of availability of decision support tools in this scenario, another important

theme that emerged was the general lack of technology use by pharmacists in the HMR

process. Although pharmacists were willing to consider the use of technology, the researcher

considers that the 'technology-poor practice' in the community signals the need for a paradigm

shift, but also has implications for what technology approach would be useful.

The last theme to emerge, but one which was of significant importance to design and

implementation strategies, was that of the 'viewpoints' of professional practice tools. The digital

document and its intentions were fundamentally different to those of the GP desktop systems

and the current pharmacy dispensing systems – the quest for a shareable, current medication

record does not fit well with the design approaches of these existing systems. This mismatch

of intentions poses a significant issue for integration of the digital document and these

systems.

From the perspective of the information model, the hospital medication elements were a

relatively good fit, with a few changes. The major changes to the model were additions of

patient-related information elements, in particular, the reasons for referral and supporting

patient physical information (e.g. falls etc.). These are information elements that are generally

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available to hospital pharmacists from patient case notes or other health professionals. So in

a way, these extensions to the model reflects a need for the same type information by

community and hospital pharmacists, although the acuity of the patients has an effect on what

this information might be – for a hospital patient this may be about a stroke suffered by the

patient, but for a community patient it may be about the management of chronic pain. An

important change to the digital document was that the researcher made ‘context-aware’ –

based on whether it was being used by the GP for referral, or pharmacist for the HMR – an

important step towards supporting individual use.

This chapter has discussed and analysed the changes to the hospital-based information model

after testing by HMR pharmacists. What the artefacts of this project – the information model

and the digital document – now required were testing in actual use.

The field studies which assessed the suitability of the community-aware model, the ability of

the digital document to support information sharing; and any impact on the HMR process are

described in Chapter 7.

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Chapter 7

Evaluating the digital document: field studies

7.1 IntroductionChapter 6 discussed the benchtop testing by Home Medication Review (HMR) pharmacists

which laid the foundations for modifying the hospital-based information model and XForms

prototype to suit a community-based context. The benchtop testing phase also further explored

the questions raised in the hospital scenario and sought answers to some more focused

questions about the use of technology for HMRs.

This chapter describes Part 2B of the project, the third and final iteration of the investigation

which evaluated the digital document prototype. The empirical research undertaken in this

phase provided the answers to the last three research questions.




These questions were answered by field testing the digital document as an intervention into

HMRs carried out in the community. This chapter reveals how the digital document was used

by pharmacists and General Practitioners (GPs); their impressions of the digital document; the

impact of the intervention; and the roles played by the information model and digital document

in the intervention.

The full analysis of these field studies is reported in Appendix X. Additional forms the

researcher needed to develop during the field study – a GP practice-specific patient consent

forms; user log-in guide; and a patient data collection form – are shown in Appendix Y.

As with the previous data chapters, the full technical aspects are described separately in a

number of appendices summarised in Table 7-1.

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• how the data were gathered is reported in Section 7.2

• a structured analysis of the data is presented under themes, consistent with the previous

two chapters, together with a report of field use and an evaluation of the intervention in

Section 7.3

• Section 7.4 discusses the changes that occurred to the information model as a result of

the field studies

• the impacts of the field studies on the digital document and server service are discussed

in Sections 7.5; and


7.2 The data gathering processThe data gathering process was considerably more varied during this phase of the research

than was the case for either of the two previous scenarios. For this scenario, the enrolment

process was considerably longer and more complex; and the data sources were more diverse.

Further, there were issues which affected both the success of enrolment and the collection of

data. Consequently, enrolment, data sources; and the issues which had an impact on the

conduct of this phase of the project are discussed separately in the following subsections.

7. 2.1 Enrolling the participantsPrior to the recruitment process, potential pharmacist participants for the field studies were

identified through the group of pharmacists involved in the previous benchtop scenario and

through personal communication with Pharmacy HMR Facilitators for the Divisions of General

Practice.

The recruitment process began with the researcher contacting the potential pharmacist

participant. As pharmacists agreed to participate, they were asked by the researcher to

nominate relevant GPs who might also be interested in participating in the field study (the GP,

in turn, was able to suggest still further pharmacists). This process resulted in an informal

'network' of participants.


Appendix Content

Z Full technical and development details.

AA XForms document code.

AB Patient XML file structure.

AC XSL (report) code.

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The researcher organised formal, face-to-face meetings with GPs to assess their interest in

participating in the field study, as well as to agree on how patient confidentiality (and server

security) would be addressed. This meeting also served to obtain agreement on the process

for their involvement and on how continuing communication between GPs and the researcher

would be handled.

The field test also involved two Hospital Outreach Medication Review (HOMR) pharmacists,

once again initially recommended by a pharmacist previously enrolled in the benchtop testing

phase; and then these pharmacists were also approached directly by the researcher. The

involvement of HOMR pharmacists was a serendipitous, but valuable, event, because the

HOMRs provided a unique opportunity to test the digital document’s effectiveness with

medication-related information concerning hospital patients about to be discharged into the

community.

It is pertinent to briefly describe the HOMR process at this point in the chapter, before any

analysis of the digital document use in that setting. The HOMR project was a component of a

larger Chronic and Aged Care project, funded by the Australian Federal Government. The aim

of the HOMR project was to facilitate an HMR for individuals who were elderly, or who had

chronic illness, soon after hospital discharge (the HMR process was discussed in Chapter 6).

These hospital patients were targeted because they were believed to be at special risk of

adverse events after hospital discharge. The HOMR project aimed to incorporate additional

HMR referral information into an existing Medication Transfer Summary form (MTS) already

developed by the hospital pharmacy; and send it to the GP, who could use the document as

the basis for an HMR referral. Part of the HOMR pharmacists' role was to liaise with the

patient's GP and ensure there was an accredited pharmacist who could provide an HMR in an

appropriate time frame (1-2 weeks after discharge).

In summary, then, from a total of 10 pharmacists and 8 GPs contacted as potential participants

in the field studies, 6 pharmacists and 5 GPs were finally enrolled. Four of the 6 pharmacists

were involved in the HMR process; and 2 were part of the HOMR project. The recruitment

history (for both GPs and pharmacists) is summarised in Appendix X.

Patient enrolment was usually handled by GPs – but some patients were also enrolled by

pharmacists (with the approval of the patient's GP). A total of 47 patients were enrolled in the

field studies.

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7. 2.2 Data sourcesData for this phase of the research came from five primary sources:

• field use of the digital document by pharmacists and GPs;

• digital document testing by HOMR pharmacists in the hospital discharge setting;

• interviews with GPs;

• a detailed examination of relevant, de-identified patient data, medication review referrals

and reports – complementing the document analysis which was done in the hospital-

based and bench-top testing phases of exploration; and, finally,

• a focus group conducted with pharmacists at the end of the field studies, to enable a

deeper exploration of the issues arising from prototype use.

Although the field studies were the principal test of the digital document intervention, further

sources of data emerged during the field activities (in addition to the sources of data mentioned

above), including: attendance by the researcher at accredited pharmacists' meetings;

conversations and meetings with various individuals involved with, or interested in medication

reviews; and logs of telephone calls and email communication.

In keeping with the Design Research method, the researcher retained data from all interactions

with participants (the complete data set for this scenario is shown in Table 7-2). The tools used

for data collection during this research phase are contained in Appendix G.

Not all these data, of course, contributed directly to the evaluation of the model or digital

document. They did, however, add to the researcher's general understanding of the

medication management environment; and the likely role of this technology intervention.

These data sources are described in the following subsections.

7. 2.2.1 Field use of the digital documentData resulting from field use of the digital document by pharmacists and GPs was collected

from the individuals concerned by the researcher, each time the digital document was used for

Table 7-2: Summary of data sources from the field studies

Data source

Field use of the digital document by pharmacists and GPs.

Hospital Outreach Medication Review (HOMR) testing.

General practitioner interviews.

Patient-related data (HMR referrals and reports).

Accredited pharmacists’ meetings.

Other incidental conversations and meetings.

Logs of telephone calls and email communication.

Pharmacist focus group.

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an HMR case: in some cases pharmacists notified the researcher the digital document had

been used; while in those cases where the researcher acted as the 'interface' between the GP

and the pharmacist, the researcher followed-up the pharmacist to check on usage. Data were

collected for a total of 28 HMRs. One pharmacist also suggested trialling the digital document

in an Aged Care Facility for Residential Medication Management Reviews (RMMRs), resulting

in additional data collection for 3 RMMRs. There was a great deal of variability in the way data

were collected from pharmacists and GPs – this is discussed in Sub-section 7.2.3.

7. 2.2.2 HOMR testingData collection for the HOMR scenario was very straightforward compared with the HMR

setting and consisted of a meeting with the HOMR pharmacists where the researcher sought

feedback about their experiences with the digital document. The value of testing the digital

document within the HOMR process was that the document had already been modelled for an

HMR referral – i.e. it was ‘ready’ to be used in the community. This scenario resulted in the

testing of 16 HOMRs.

7. 2.2.3 General Practitioner discussions and interviewsThe meetings with GPs provided the researcher with a range of data including data which was

important to the conduct of the project, such as how patient confidentiality and data security

needed to be addressed; and how the researcher would communicate with the GP during the

project. However, the data that emerged from these meetings also pertained to: GPs’ overall

impressions of the project; views on current HMR practices (including problems and potential

solutions); feedback on the digital document prototype (demonstrated either on a notebook

computer or as a paper example based on the opportunities afforded to the researcher); and

business and other issues that impacted on HMR practices.

7. 2.2.4 Patient-related data used for the trialPatient-related data collected by the researcher included paper copies of HMR referrals and

reports and, where possible, copies of the corresponding XML files from participants'

computers. These patient XML files were generated by the digital document when participants

used the digital document to enter referral information, or information for a report. Patients

were de-identified by the pharmacist or the researcher, as previously agreed with the GP and/

or pharmacist.

The paper HMR referral document identified the principal information provided by the GP. In

addition, the difference between the information contained in the GP's paper referral and the

pharmacist's XML referral file provided insight into what information was, or could be, entered

into the digital document. The GP's referral document also revealed what information was

missing and provided a basis for identifying which decisions the pharmacist might have made

in deciding which information from the document would be used.

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The researcher used the same strategy of collecting all possible paper documents in the case

of reports as well (i.e. both paper documents and XML files) to ensure that the information

entered into the digital document following the HMR reflected what had actually been sent to

the GP. This ensured there were no additional hand-written entries on the paper copy reports

sent to the GP, or to observe if additional information had accompanied the paper report (e.g.

information pamphlets). The researcher also anticipated that using XML files would allow

easier comparison of information elements used between patients – and this was the case.

7. 2.2.5 Accredited pharmacists’ meetingsAttendance at these meetings provided the researcher with valuable insights into both the

HMR process as well as identifying issues common to HMR pharmacists. The researcher was

first invited to attend a meeting on HMR software availability in June 2004, well before the

commencement of the field studies themselves. This led to subsequent attendances at (6)

other meetings relevant to the project which were presentations on HMR-related topics

(Quality Assurance featured highly) and contained case studies of HMRs as practical

exercises for the HMR pharmacists. One meeting was attended by a GP and another by a

clinical pharmacologist – and these two meetings provided further valuable data on doctors’

perceptions of the HMR process.

7. 2.2.6 Other conversations and meetingsOne serendipitous outcome of the project was the networking with other pharmacists and

individuals interested in the project. In addition to providing material which confirmed the

project's approach, these encounters were also excellent sources of ideas for further research

– particularly important for verifying the value of the project – for example:

• interest in the project's modelling approach by a Division of General Practice HMR

project group

• meetings and conversations with Pharmacist Facilitators (endorsing the direction of the

project)

• interest from the Head of a Clinical Pharmacology Department at a metropolitan adult

hospital which is leading a discharge project involving cardiac patients; and

• meetings with lecturers at the University of South Australia's School of Pharmacy and

Medical Sciences, who were interested in potential applications of the digital document.

7. 2.2.7 Logs of telephone calls and email communicationTelephone calls were normally used by the researcher to arrange meetings, follow-up on

previous meetings or to discuss practical aspects of the project with participants. The log of

project-related telephone calls contained primarily administrative data and is therefore not

discussed explicitly in this chapter – although any information obtained from telephone calls

which was useful to the project has been incorporated into other discussions

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Email communication with participants was used by the researcher wherever possible, not only

because this provided a written record of communications, but also because, as an

asynchronous negotiations medium, it was far less intrusive into the participants' busy

schedules than, for example, telephone calls or face-to-face meetings. As with telephone calls,

the record of emails is not reported here because of its size and nature but, as with the

telephone log, any information useful in the context of the project is included in other

discussion.

7. 2.2.8 HMR pharmacists’ focus groupThe focus group, which ran for approximately 1.5 hours, was held at the end of the field study

and was attended by 3 of the 4 HMR pharmacists. A summary of the focus group findings was

circulated to all participants for verification and to ensure the major issues had been

adequately captured. The one pharmacist who was unable to attend the focus group was

subsequently interviewed by the researcher, enabling him to comment on issues from the

focus group, as well as providing his feedback on the prototype testing more generally.

Although these field studies began with a simple plan for the data gathering process, the many

practice differences of pharmacists and GPs made this process more complex than

anticipated. Some of the issues contributing to this complexity are discussed in the next sub-

section.

7. 2.3 Issues encountered during data gathering

7. 2.3.1 Field studiesBecause of the different HMR practices of GPs and pharmacists, their level of involvement in

the field study needed to be flexible, being based on their level of comfort with the use of the

digital document (and technology in general); and on how they believed this might fit into (or

change) their work practice.

This resulted in a range of different 'paths' for the digital document during the field studies,

depending on whether the server service was used and how the digital document was used –

and, consequently, affecting the quantity and quality of the data available to the researcher

(e.g. where the referral was sent by the pharmacist directly to the researcher, there was no

ability to evaluate the GP's experience of entering data into the digital document).These digital

document paths are summarised in Table 7-3.

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7. 2.3.2 HOMR testingAlthough hospital environment provided an ideal opportunity to test the server service

(because of the networking and Internet access in place), the HOMR project pharmacists did

not use the server service – stating this was because of time commitments. The researcher

did detect a level of discomfort from one pharmacist about server use, although the reason for

this discomfort was unclear. Perhaps one explanation was that patient information entered into

the server would be stored 'elsewhere' (leading to unvoiced concerns about patient privacy).

Consequently, the VB viewer was installed on two PCs within the pharmacy department; and

testing by the pharmacists occurred quickly after this.

7. 2.3.3 Meetings with GPsIt has already been mentioned that differing requirements between one general practice and

another prevented complete data collection, but a number of other issues which arose during

meetings with GPs affected the conduct of the project.

One minor issue (easily resolved) was that most GPs required a patient consent form for use

in their practice – these forms are shown in Appendix Y.

Table 7-3: The digital document paths in the field studies

GP and Pharmacist IDs

GP1 and P1 GP1 and P2GP faxed referral to pharmacist who entered detail into

notebook computer. Report done on notebook and paper copy faxed back to GP.

(GP1 did not want patient data entered onto server)

GP faxed referral to pharmacist who entered detail into notebook computer. Report done on notebook and paper

copy faxed back to GP.(GP1 did not want patient data entered onto server)

GP2 and P4GP mailed the referrals to the researcher who added them to the server. The researcher added the patient files to the pharmacist’s computer – the pharmacist did not want to use the server directly. The amended patient files were taken from this computer and loaded back onto the server, but a paper report was delivered to the GP by the pharmacists.

The GP did not use any on-line access

GP3 and P1 GP3 and P3

For one HMR patient, GP faxed referral to pharmacist. Pharmacist used local browser to enter referral information and report. Paper copy of report sent to GP by pharmacist. For three ACF patients, the pharmacist entered information for the HMR reports using local browser, and sent paper

copies to GP

GP faxed referral to pharmacist. Pharmacist used local browser to enter referral information and report. Paper copy

of report sent to GP by pharmacist.

GP4 and P4GP emailed the referrals to the researcher who added them to the server. The researcher added the patient files to the pharmacist’s computer – the pharmacist did not want to use the server directly. The amended patient files were taken

from this computer and loaded back onto the server to allow GP on-line access.

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One theme which has clearly been significant throughout this project is that of time and its

impact on the HMR process. A rather different impact of time was on the conduct of the project

itself. Lack of time was the reason given by 3 of the 8 GPs (contacted as potential participants)

for not participating in the field studies. Using the same justification, only one of the remaining

five GPs used the digital document personally. All five GPs were happy to have their patients

considered for inclusion in the studies although, here again, one GP claimed he was too busy

even to obtain consent from patients (this was to be done by the researcher or the HMR

pharmacist). The main reason for GP involvement at all was their common desire to be able to

help improve the HMR process in any way – for some GPs, the whole issue was about patient

care but, for others, the major focus appeared to be on improving their business processes.

This focus on lack of time also affected the researcher's meetings with GPs. During the field

studies the researcher was acutely aware that GPs expected him to waste as little as possible

of their time, which meant that interviews with GPs were not as valuable to the project as they

could have been. And, although a demonstration of the digital document (on a laptop

computer) had been planned for all GP participants, only two of the GPs ultimately participated

in such a demonstration. In fact, GP-researcher communication always occurred with the

practice nurse who acted as an intermediary, except in the case of one GP with whom there

was direct communication and with whom meetings were of sufficient length to enable

appropriate data collection.

Finally, although a final (exit) interview had been planned for all GPs, this took place only with

one GP in person – though a second GP's practice provided a telephone interview (with the

practice nurse!).

A summary of the researcher’s interactions with GPs and their involvement is shown in Table

7-4.

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7. 2.3.4 Patient-related dataThe wide variability in HMR practices amongst GPs and pharmacists described earlier meant

that collection of documents (or patient XML files) could not be achieved in a consistent

manner.

For HMRs, a copy of the paper referral was obtained for all (28) patients. There were several

possible avenues for the paper HMR referral documents, each with different implications for

data analysis. The paper referral could be sent:

• to the researcher (this occurred when the researcher was acting as the 'interface'

between the GP desktop system and the digital document – entering the referral

information into the digital document on the server so it could be accessed on-line by the

pharmacist). Where the information was entered into a digital document by the

researcher, it was the same information that was contained on the paper referral;

Table 7-4: Summary of interaction with GPs

GP Practice details / background Summary of interaction Level of

involvement

GP1 Shared practice with Practice Nurse. Site had been compulsory acquired and was in the process of negotiation. Practice was to go ‘paperless’.

GP was very interested in use of technology. No initial interest due to lack of time and no interface to GP desktop system. After first meeting was happy to involve patients and nominated other pharmacists. Did not want patient data stored on project server. Despite much communication with the Practice Nurse (email), no further meetings eventuated due to time commitments.

First meeting.Seven patients.

GP2 Shared practice with Practice Nurse.

Agreed to participate based on no changes to his existing process. Referrals to be sent to researcher by mail to enter into the server service. Nominated local pharmacist. Some communication by email with Practice Nurse. Had final interview.

First meeting and final interview.Five patients.

GP3 Single practice with Practice Nurse.

Meeting with both where they agreed to participate based on current process. Subsequently demonstrated digital document on notebook to Practice Nurse. Communication occurred through Practice Nurse (email and phone). There was confusion about the HMR process at this practice. Final interview unable to be organised.

First meeting with subsequent demonstration of prototype on notebook.Two patients; and additional three patients for RMMR.

GP4 Single practitioner. First meeting with demonstration of digital document; and agreed to participate. This GP had not previously done HMRs. The GP’s notebook was set up for local and server use of the digital document. There were five meetings including the final interviews, and communication occurred with the GP throughout. The GP provided a written evaluation.

Total of five meetings. GP use of the digital document locally and via server. Fourteen patients.

GP5 Shared practice with Practice Nurse. Same practice as GP2.

First meeting with demonstration of the prototype. Agreed to participate based on no changes to existing process; and researcher / pharmacist to obtain patient consent.

First meeting. No patients.

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• to the pharmacist, in which case data could only be collected by the researcher after the

HMR was completed – so that the (XML) file represented the situation after the HMR, i.e.

it was the report, not the referral. In these cases, there was no opportunity to see what

information the pharmacist had entered into the digital document compared with that

contained in the paper referral. In the case of the (3) RMMRs, there was no paper copy

of a referral, as the GP arranged these by telephone; or,

• not at all, as was the case for the HOMR scenario. For the (16) HOMR patients, there

were only pharmacist-generated (XML) referral files, as the pharmacist was responsible

for generating the referrals.

For HMR reports, both a paper copy and a matching XML file were available for all HMR

patients (in the sole exception, a pharmacist sent additional (paper) drug information material

to the GP).

A summary of all medication review documents collected during field studies is shown in Table

7-5. The numbers in the table represent the number of documents (or files) collected by the

researcher out of the total possible, i.e. the number of patients.

.

These inconsistencies made it impossible to compare 'before' and 'after' information from the

referral and the report. It was possible, however, to analyse which information elements were

missing from the referrals, how often they were missing; and how this might be influenced by

the information sources available to the pharmacist – missing information is discussed in

Section 7.3.1.

Further, the reporting 'style' of the pharmacists did not really change before or after the

intervention – pharmacists used the digital document to prepare a paper-based HMR report

very similar to that they were using prior to the intervention – which prevented the researcher

from evaluating the HMR reports (using the HMR QA form – see Appendix C) with an

independent panel to assess HMR report quality.

Table 7-5: Patient data sources

HMR HOMR RMMR

Paper referral 28/28 NA NA

XML referral file 20/28 16/16 NA

Paper report 3/28 NA 3/3

XML report files 28/28 NA No

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7. 2.3.5 EmailAlthough email appeared to be the ‘ideal’ communication medium with which to capture

researcher-participant (remote) interactions, email use varied between participant groups and

was not as useful as anticipated.

All pharmacists had access to email, either at work or at home. Email use was not a regular

practice for all pharmacists, however, but was used effectively by four pharmacists.

All GPs had email addresses for their practices, but messaging was usually done by the

Practice Nurse, rather than by the GP. In these cases, it was often not clear whether the

message had actually been received by the GP – for some, therefore, there was still a need

for follow-up telephone calls from the researcher. For three GPs, email was used to deliver

draft patient consent forms. One notable exception – the most technology-aware GP – used

email directly and effectively, both to communicate with, and to deliver patient referrals to, the

researcher.

7. 2.3.6 The focus groupThe focus group had been planned to include both pharmacists and GPs involved in the

project. In the event, however, no GPs were invited to attend the focus group, because time

constraints made it unlikely they would be able (or willing) to do so.

In summary, the data gathering process did not proceed for the project as expected and

compromised the researcher's ability to collect and evaluate (some) data. The final number of

patients cases used to test the digital document was 47, comprising: 28 HMRs; 3 Residential

Medication Management Reviews (RMMRs); and 16 HOMRs. Attention turns next to the

analysis and discussion of this data in Section 7.3. Participants are referred to in this chapter

using abbreviations, e.g. P1 and GP1 for pharmacist one and GP one respectively, to maintain

anonymity.

7.3 Analysis and discussion of findingsAs with the previous two chapters, time and space constraints prohibit the fully detailed

analysis of the material gathered for this chapter. A full analysis is, however, contained in

Appendix X.

The approach to analysis in this scenario was different to that taken in the previous two

scenarios in several ways. Firstly, there were no formal questionnaires to analyse. Secondly,

this phase was designed to observe the effect of the digital document intervention on

medication management as it occurred. Thirdly, the overall goal of this phase of the research

was to determine the contributions of the information model and the digital document.

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Impressions of these effects were determined as a combination of the more specific feedback

about use of the digital document (and, naturally, the underlying information model); and the

researcher's analysis of the many and varied sources of data.

This chapter once again makes use of thematic headings within which to discuss the results,

as was the case for the previous two chapters. Some themes which emerged in this scenario

were (not surprisingly) the same as those identified in the benchtop scenario. However, the

ability of the researcher to directly investigate the 'other side' of the HMR equation – the GP –

allowed some of these themes to be further developed and revealed others. The themes which

frame the discussion are shown in Table 7-6, where it is clear that both 6.3.10 and 6.3.11 are

new themes.

7. 3.1 Missing informationIt appeared possible the researcher might be able to measure the extent of missing information

in the field studies since, although overall document collection was incomplete, HMR referral

documents were obtained for all (28) patients

A detailed tabular comparison of missing information is contained in Appendix X. The

discussion in this chapter will, of necessity, only summarise this comparison, but some

sections of some tables in the appendix have been reproduced here where they contained

especially important observations.

One particular difficulty for the researcher was attempting to measure whether missing

information was important, i.e. whether its absence was an issue for patient care. For example,

if a laboratory result such as an INR was missing for a patient taking warfarin, it was impossible

to know whether this omission was acceptable because the patient had been stabilised on


Section Theme

6.3.1 Missing information

6.3.2 Information granularity and the language of health professionals

6.3.3 Conversation and communication

6.3.4 Time constraints and summary information

6.3.5 Alerts & reminders

6.3.6 Systems for experts rather than expert systems

6.3.7 A technology-poor practice paradigm

6.3.8 The ‘viewpoints’ of professional practice tools

6.3.9 Pharmacists’ perceptions of GPs in the HMR process

6.3.10 The Practice nurse

6.3.11 Complementary medicines & Over-the-counter medication

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warfarin for some time (if the patient had only recently commenced taking warfarin and there

was no recent INR, it was clearly both relevant (and important) that this laboratory value be

provided). To resolve this problem, the researcher introduced a number of categories to

describe the presence of information elements, including:

• yes – information was entered

• not entered (ne) – there was a heading in the referral source for this information, but no

information was provided. This information may not be relevant for the patient.

• no – no heading for this information in the referral source, so that no information could be

provided

• to follow – this was information which could be conveyed via other sources (e.g. the

referral letter from the GP)

• NA – not applicable (e.g. a referral reason in the RMMR report).

Some information on the referral could be implied – sex, by 'Mr.' or 'Mrs.' (although not where

the patient's title was 'Dr.' or 'Prof.'); and medication route from the type of medication product

(e.g. a tablet would generally suggest the oral route of administration). One GP also included

additional information elements which were not part of the information model (e.g. pulse rate).

The discussion of some aspects of information availability follows in the next sub-sections,

based on the major information categories of the information model, i.e. referral, personal,

treatment, medication; and laboratory information.

As described during the discussion of bench-top testing in Chapter 6, specific reasons for

referral (Table 7-7) were infrequent and, even when provided, were still framed in Health

Insurance Commission (HIC) terms (i.e. medication risk factors). Of course, there may not

have been any specific issues of concern for these patients. For HOMRs, the hospital

admission was reason in itself for an HMR follow-up in the community, although pharmacists

did list other specific patient issues as well. For the RMMRs, a review was a routine event, so

that a specific referral reason was not required.

Table 7-7: Comparison of missing information in referral documents – referral information

Information type (document page)

Information element

HMR (28) HOMR (16) RMMR Reports (3)

Referral information

referral description

yes (standard reasons) - 5/28yes, free text - 7/28to follow - 5/28no - 11/28 (10 from same GP, but perhaps later via referral letter).

yes - 15/16ne - 1/16Individual reasons (for admission) as well as the summary above.

NA

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A substantial amount of personal patient information could be missing (see Table 7-8); and the

use of certain terminology could create uncertainty about the information which had been

provided. In the case of allergies, for example, the term 'none known' was often used – which

is not at all the same as 'none': 'none' means that this patient has no allergies; but 'none known'

does not make it clear whether allergies have been ruled out or not. Weight was another item

which was also frequently missing. This was problematic because weight is the basis for

checking doses and performing a number of important calculations (e.g. BMI). The tables also

show that for some missing HMR information (e.g. weight, height), there appeared to be a

pattern based on the source of the referral information – this is discussed in detail in Section

7.3.8 (the 'viewpoints' of professional practice tools).

HOMR pharmacists, in theory, had access to any hospital-based information they required. In

reality, however, these pharmacists could experience the same missing information issues as

their colleagues described in the hospital scenario (see Chapter 5) but because they did not

need to make prompt decisions about therapy, they had more time to find the missing

information (in fact, these pharmacists made no mention of missing information). Nonetheless,

certain information was only entered if the pharmacist felt it relevant for the patient, e.g. a

serum creatinine level would only be entered if there was an issue about renal function. So,

although some information appeared to be missing, it was possible these lacunae were

deliberate omissions by the pharmacist.

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.

Table 7-9 provides a summary of missing treatment-related information within the different

types of medication management review. The reporting of treatment information for HMRs is

actually misrepresented in this table, however, because treatment information could be

contained under either 'active problems' or 'history', depending on where GPs had initially

entered this information within their desktop system (over which the trial had no influence).

Only 4 HMR referrals listed information under both the active problems and history heading –

giving a true indication of the patient’s disease status. One referral contained no treatment

information at all – providing the pharmacist with no basis against which to judge the

appropriateness of the medication prescribed for the patient.

Table 7-8: Comparison of missing information in referral documents – personal information


Information element


Personaldob(date of birth)

yes - 21/28no - 7/28 (these were not supplied with an alternative age below).

yes - 8/16: ne - 8/16 yes.

age NA - 21/28 (as dob was entered)no - 7/28

age - 5/16 (de-identified) ne - 11/16

NA.

sex no - 28/28, on lab. reports if they were provided

yes - 12/16: ne - 4/16 yes.

weight yes - 7/28: no - 21/28 yes - 6/10: ne - 10/16 yes

height yes - 7/28: no - 21/28 yes - 4/16: ne - 12/16 ne. As above.

BP yes - 7/28: no - 21/28 yes - 12/16: ne - 4/16 ne. As above.

Se creat yes - 8/28no - 20/28

yes - 8/16ne - 8/16

ne.As above.

allergies yes - 28/28(many were ‘none known’).

yes - 10/16ne - 6/16

ne.As above.

ADR (warnings)

yes - 5/28: no - 19/28ne - 4/28

yes - 4/16: ne - 12/16 yes. Stated ‘nil known’ in all cases.

recreational subs

yes - 12/28no - 16/28

ne - 16/16 ne.

Physicalfalls no - 28/28 yes - 1/16: ne - 15/16 ne.

cognition yes - 7/28: no - 21/28 ne - 16/16 ne.

memory no - 28/28 ne - 16/16 ne.

language, dexterity, vision, hearing, swallowing

yes - 7/28no - 21/28

ne - 16/16 ne.

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A medication list (Table 7-10) was the information provided most consistently on the paper

referrals – although even this was missing on two occasions!

The source of medication information was a 'dump' from the GP desktop system output under

four headings in the report:

• drug name (actually a product name from the medication list available within the GP

desktop system)

• Ltd.Elapse (the purpose of this is unknown, as nothing ever appeared under this

heading)

• Strength (this could duplicate information contained in the drug name); and

• Dose/Freq./Special (this heading concatenated all dosing frequency and additional

information – an example of the information that could be listed under this heading is: '2

inh q.4.h. p.r.n.'). These information components reflected the abbreviated pick lists of

instructions available within the GP desktop system.

Although pharmacists tended to separate 'regular' from 'when required' medications in HMR

reports, these divisions were never used in the referrals they received; and very little social,

family, or compliance information was provided to pharmacists.

The HOMR entries were more detailed because information was tailored by pharmacists and

this information often included additional instructions – both with Latin abbreviations, as well

as with additional English phrases e.g. '2 puffs inh bd rinse mouth after dose and inhale via

spacer'.

Table 7-9: Comparison of missing information in referral documents – treatment information


Information element


Treatmentactive problems

yes - 13/28: no - 14/28ne - 1/28

yes - 15/16: ne - 1/16 ne.

history yes - 18/28: no - 10/28Some used history for all problems.

yes - 15/16: ne - 1/16 ne.

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Laboratory information (Table 7-11) was not provided regularly by the GP and, where it was

provided, was included in a separate paper document printed from the laboratory reports

stored in the GP desktop system. HMR pharmacists tended not to add any laboratory values

(from the paper sources) into the digital document for reporting back to the GP, so that

laboratory values seldom ended up in the digital documents. By contrast, the HOMR

pharmacists did enter laboratory values when they were considered important for

communicating to others (which was precisely the reason for including this section in the digital

Table 7-10: Comparison of missing information in referral documents – medication information


Information element


Immunisationstetanus yes - 9/28: no - 11/28

ne - 8/28yes- 2/16: ne - 14/16 ne.

flu yes - 17/28 (some were extensive records).no - 11/28

yes - 2/16ne - 14/16

yes - 1/3ne - 2/3

pneumococcus

yes - 17/28: no - 11/28 yes 2/16: ne - 14/16 yes - 1/3: ne - 2/3

immun. Dates

yes - 16/28: no - 12/28 ne 16/16 yes - 1/3: ne - 2/3

Medications-regular

date no - 28/28 two had no medication list at all.

yes - 6/116ne - 10/16

no.

generic yes - 22/28: no - 6/28 yes - 15/16: no - 1/16 yes.

brand yes - 22/28: no - 2/28 yes - 14/16: no - 2/16 yes.

dose yes - 26/28: no - 2/28 yes 16/16 yes.

route yes - 6/28: no - 3/28no (but implied from medication form) - 19/28

yes - 16/16 yes.

frequency yes - 25/28: no - 2/28no (but implied) - 1/28

yes 16/16 yes.

instructions yes - 6/28: ‘mdu’ - 11/28no - 11/28

yes - 14/16: no - 1/16ne - 1/16

no.

indication yes - 2/28: no - 26/28 yes - 14/16: ne - 2/16 no.

duration yes - 1/28: no - 27/28 yes - 13/16: ne - 3/16 no.

Medications-prn.

no specific prn list. yes - 7/16: ne - 9/16 ne. One patient did have prn medication.

HistoriesSocial yes - 3/28: no - 19/28

ne - 6/28ne - 16/16 ne.

Family yes - 2/28: no - 19/28ne - 7/28

no - 16/16 ne.

Compliance no. yes - 9/16: ne - 7/16 ne.

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document).

In summary, missing information was as serious a problem as originally anticipated, with a

clear reliance on the GP (often with an unsuccessful outcome). Pharmacists, however,

appeared to be resigned to the fact that this would occur and would carry out the review despite

any missing information – there was little evidence of pharmacists contacting GPs to fill in

information gaps in their referral documents. A printout of the dispensing history from the local

pharmacy was, however, used to supplement medication information if required.

The focus on chronic disease management also seemed to alter the importance of missing

information because, as these patients were not acutely unwell, pharmacists assumed that the

missing information would be unlikely to have much immediate impact on the patient's

management. Since, although this was a small study, no cases of patient misadventure were

reported, missing information in a community setting may indeed be less important than in the

hospital environment.

An interesting missing information pattern in relation to the report used from GP desktop

system is discussed in detail in Section 7.3.8.

As the HMR system exists now, there is no incentive for GPs to have complete information in

their desktop system – pharmacists will simply cope with this lack and come back to the GP if

there are any major problems. GPs' demand for a summary of issues (despite their

consistently vocalised desire for a complete, current medication record) suggests that this

situation is unlikely to change.

Nevertheless, pharmacists saw an opportunity to collect a complete set of information by

sharing the digital document with GPs (and other pharmacists involved in the patient’s care),

believing that this would allow better decision-making about the patient. Overall, this problem

of missing information further reinforced the notion that the document could only suggest and

support inclusion of information elements, not mandate that health professionals use them.

Table 7-11: Comparison of missing information in referral documents – laboratory information


Information element


Laboratorydate yes - 8/28: no - 20/28 yes - 10/16: ne - 6/16 ne.

item yes - 9/28: no - 19/28 yes - 16/16 ‘no results’ - 3/3/

result yes - 8/28: no - 19/28ne - 1/28

yes - 10/16ne - 6/16

ne.

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7. 3.2 Information granularity and the language of health professionalsThe issue of information granularity – the need for the provide information elements at different

levels of detail to support the pharmacists' natural work processes – was raised in the hospital

phase (Chapter 5) and confirmed in the benchtop testing phase (Chapter 6). The researcher

believes the need for information elements at different levels of granularity was further

confirmed by the field studies, although this confirmation was more implicit than explicit. The

GPs accepted the content of the digital document without further suggestions for changing the

nature of the information elements – and both the pharmacists and the single GP who made

use of the digital document directly commented on the appropriateness of the information

elements which the digital document provided.

A further factor emerged during the field observations. Pharmacists and GPs commonly used

abbreviations, acronyms and personal 'shorthand' when entering diseases and symptoms, or

as part of the clinical narratives entered into referral or report documents (as well as the

common use of Latin abbreviations for directions for medication use). This, of course, also

happens in the hospital setting but, as the clinical narrative text itself was not the subject of

investigation, this issue was not as apparent as it was in the field studies setting.

Examples of clinical narratives and expressions used during field studies included:

• In HMR referrals from GPs

‘Breast cancer (left), radiotherapy/axillary lymph node clearance/tamoxifen – 2000’

‘Necrosis – infection, post radiotherapy’

‘Scaphoid Fracture (left), got lateral epicondylitis from POP’

• In HOMR referrals (from a pharmacist)

‘Lipid studies were suboptimal – consider introducing a statin, if an appropriate trial of lifestyle

and diet modification does not produce improvements’

• In HMR reports

‘CCF, IHD, PCI to LAD’

‘It was also noted that Ostelin is on the medication list. Mrs W's free Calcium is at the lower

end of normal i.e. 1.11 (1.10-1.25). On this basis, it may be worth considering the addition of

Calcium.’

There is clearly the possibility of supporting the use of acronyms for diseases (e.g. CCF)

through dictionaries, or using terminologies (such as SNOMED CT1). This possibility is unlikely

to be successful, however, if GPs (or pharmacists) need to navigate through enormous

terminology lists to locate the clinical terms that they require (and if this processing power

1. SNOMED CT® is a clinical, computerised language designed to enable unambiguous communication between health care institutions and professionals.

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existed in GP’s desktop systems).

Another issue was the use of free text fields: both HMR and HOMR pharmacists commented

positively on this feature, as it allowed flexibility in terms of what – and how much – information

could be entered into the document. Free text fields were considered more desirable than

drop-down template text for reporting, because drop-down fields can: make reports appear too

similar, do not easily allow pharmacists to express their clinical judgement; and could direct the

nature of the report in a manner which was not intended.

The use of passages of text thus presents some particular problems for the design of decision

support tools. Firstly, how could structured lists be used to compose meaningful (and readable)

clinical narrative. Secondly, the information exchanged between these health professionals

requires a knowledge of other patient details – the patient context – if it is to be meaningful to

health professionals. Meaning occurs now through health professionals using their commonly

shared and understood ‘language’.

The researcher also gained the impression from pharmacists' meetings that the amount and

nature of the information to be provided back to the GP should include whatever is important

– this leaves the notion of any data structure quite open. It is very difficult to imagine how more

granular information elements would support pharmacists' requirements. Moreover, it is

foreseeable that any structure imposed by decision support tools on these ‘conversations’ will

be met with resistance from health professionals.

In summary, while providing support to the findings from the first two phases of the research

that there is a need to support the information granularity which best fits with the information

use of the health professionals involved in medication management, the field studies made it

clear that the information communicated by the digital document should be couched in the

everyday 'language of practice' of health professionals. The researcher therefore considers

that the dilemma facing technology which attempts to support health professionals is an

impasse resulting from the need for data categorisation to underpin decision support (e.g.

alerts) and allow information to be communicated 'seamlessly' between technology systems

(enabling inter-connectivity) – while simultaneously providing humans with simple and flexible

support to complement their work processes, without losing the high-level richness they

require in their information.

Information provided back to the GP should be ‘whatever is important’

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7. 3.3 Conversation and communicationThe opinion of the HMR pharmacists in this phase echoed the views of the pharmacists

involved in the benchtop testing phase – that issues such as GP-pharmacist relationships and

the attitudes of GPs to HMRs affected whether the pharmacist would actively seek information

from the GP.

During the field studies there were only a few occasions when pharmacists reported talking to

GPs – e.g. for one pharmacist, this involved establishing the initial HMR process details with

a GP new to ordering HMRs; and for other pharmacists, conversation occurred during

combined GP-pharmacist educational meetings. For the field study pharmacists, however,

there was little reluctance to contact GPs, compared with the reluctance expressed by other

pharmacists at accredited pharmacists' meetings and during the benchtop testing phase. Yet,

although the researcher observed that field study pharmacist-GP relationships were quite

good, communication between these two groups was still infrequent – and much of the 'front-

line' communication between pharmacists and medical practices which did occur involved a

Practice Nurse.

Pharmacists did not appear to hold conversations with other (allied) health professionals,

although it was difficult for the researcher to be entirely sure of this.

The lack of communication might have meant that the patients encountered in this field study

were straight-forward and did not require additional follow-up by pharmacists. Clearly, our

wider field study is required before any definitive comments can be made about the overall

breadth and quality of pharmacist conversations with GPs and other health professionals.

Most communication between pharmacists and GPs, therefore, occurred by means of the

paper documentation which flowed between them. This resulted in some significant delays in

the reporting of HMRs to GPs – and in GPs being unaware of whether HMR reports had been

received from pharmacists. As the researcher has already suggested during the reports of the

benchtop scenario, this presents a quandary – having the referral document function as the

sole effective source of information from the GP to the pharmacist means that this document

absolutely must be comprehensive – but this does not occur! One of the main benefits of the

digital document as perceived by pharmacists was communication – whether because of or

despite the uncertainty of the information they received – the potential to communicate (and

thus share) information more quickly between themselves and GPs was seen as an important

and useful feature.

The researcher believes there are two points to be made here. Firstly, when the digital

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document is seen as an intervention in the relationship between GPs and pharmacists, this

intervention may be realised more successful where good relationships (and communication)

already exist, as it would be easier to 'intervene' in a relationship which already has a co-

operative basis (as seen in this field study). Secondly, and perhaps paradoxically, where

pharmacist-GP relationships are uncertain, using the digital document may enable the

development of some common ground to help communication – and perhaps even improve

relationships (as suggested by field study pharmacists).

7. 3.4 Time constraints and summary informationPharmacists in the benchtop phase remarked that time was a critical issue for GPs in the HMR

process, affecting the GP's ability to order HMRs initially, as well as to deal with HMR reports

received back from the pharmacist. This issue was confirmed by these field studies: not only

by observing the impact on the HMR process, but also in terms of the (lack of) project

involvement by GPs described earlier in this section.

As GPs attempted to minimise their time demands, they expected that HMR reports would

always contain concise summaries of important information, rather than including detailed

accounts. GPs could actually be quite disparaging about detailed reports.

The unnecessary information in the HMR reports to which GPs referred also included the

addition of pharmacological or pharmaceutical detail by pharmacists (e.g. commonly-known

drug side effects).

Time was also the reason why some GPs wanted a 'one-button' approach from desktop

systems designed to initiate HMRs (although one GP considered this approach to be

undesirable, as it did not allow the patient to be properly assessed prior to the review). Lack of

time also prevented GPs from gaining a clear understanding of a patient's medication use (one

reason why GPs were reluctant to stop medications prescribed by specialists), or from

communicating changes in medications to patients (who quickly forgot these details in any

case). These two issues highlight the value of an HMR to the GP, not only to clarify medication

use, but also to uncover issues which might not be identified during the necessarily brief

Where good communication exists, so might better outcomes for patients

..it was important to keep the information succinct and report on the main points, rather than the 'small stuff’

GPs did not want to be told ‘what they knew’

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meetings between GPs and their patients.

GPs' lack of time was well understood by pharmacists, who noted that this was the reason for

poor HMR referral rates from GPs (only about 10% of all GPs ordered HMRs). Consequently,

pharmacists aimed to provide simple, practical HMR reports which would place minimal time

demands on the GP.

One topic which arose during the field studies was the amount of information 'returned' to the

GP by the (paper version of the) digital document report, compared with the amount of

information in the summary-style HMR report normally prepared by the pharmacist. Although

GPs felt that this provided too much information, in (electronic) use the structure of the digital

document would address this perception, as the 'front page' of the digital document carried

only the summary information required by the GP – the remaining information could be viewed

by the GPs if they wanted to do so.

Further, HMRs take place in a small business environment (of GP and community pharmacy

practices) with financial gains being the main incentive for some GPs and pharmacists to

engage in the practice of HMRs. The challenge for technology is to support information sharing

and communication as a balance between the quality required for safe patient care; and the

expediency required for business efficiency. Unless there is an increase in the amount of time

available for GPs to deal with HMRs, or a change in the HMR process to make it easier, GPs'

enthusiasm for HMRs is likely to remain low.

7. 3.5 The use of alerts and remindersThe benchtop focus group suggested that alerts and reminders would be of limited use (other

than perhaps for weight and height) – this suggestion was substantiated during field studies.

Missing data (again) was a central problem. For example, weight and height values were only

conveyed in the referral information on 7 of 28 occasions (25%); and creatinine on 8 of 28

occasions (29%) – and these 7 occasions for weight were all from one GP. But even when

weight was flagged as missing on the digital document when used by the pharmacist, the

pharmacist did not enter that information. Of course, there is no way of knowing if that

information would have been entered by GPs had they used the digital document directly.

Warfarin alerts were a good example of this problem, from several perspectives. 2 HMR

patients, 3 HOMR patients and one RMMR patient within the field tests were taking warfarin.

Neither of the HMR patients had an INR value in their laboratory information, causing the alert

(requesting the availability of an INR) to be displayed in the document – but no INR value was

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added to report by the pharmacist. Two of the 3 HOMR patients had INR values entered in the

laboratory information, but the text value of 'warfarin' which had been entered into the

medication list was capitalised (i.e. Warfarin), which is not the convention for generic names –

which are invariably lower case – so the warfarin-INR alert was not triggered. The ACF patient

had recently been prescribed warfarin, but there was no INR value in the laboratory information

of the report sent to the GP by the pharmacist. As with the HOMR cases, the text value of

'warfarin' was capitalised so the alert did not appear.

These findings not only showed that HMRs can fail to include crucial information, but also

highlighted a problem with the input validation of the test system (which had failed to effectively

and accurately verify text). Although the researcher had discussed these alerts with the

participating pharmacists previously, they did not even consider the alerts even when they

'malfunctioned' (as was the case with the HOMR and RMMR) – this may suggest that alerts

are not as important to the pharmacist as anticipated; and poses some important questions

about the effectiveness of these to a HMR system.

Further, as laboratory values for HMRs were provided on separate (paper) documents, values

were never entered into the digital document by HMR pharmacists. For HOMRs, values were

only entered if they were considered important. These practices served to circumvent the

alerts provided in the digital document – once again suggesting that alerts might not prove

particularly useful in the HMR environment.

In contrast, however, one pharmacist did actively use calculators – she was the recipient of the

more detailed HMR referral reports from the GP; and thus had better information available.

One can surmise that if more information is provided, there may be better use of such features.

Despite this one helpful example, this small field study suggests that alerts may not be as

useful as hoped for because of missing information and current information management

practices. However, this would need to be confirmed by larger and better controlled studies.

7. 3.6 Systems for experts rather than expert systemsThe conclusions from the hospital phase (Chapter 5) were that clinical pharmacists evolved

into specialists, characterised by high levels of use of personal knowledge during their

medication-related decision-making. The benchtop testing phase (Chapter 6) also supported

this view of accredited pharmacists. Field studies confirmed that the substantial levels of

missing information forced HMR pharmacists to use personal knowledge to a significant level

– the HMR environment is not an area for novices.

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Thus, across the continuum of medication management, the fact that we are dealing with

specialists suggests a particular approach to the design of decision support tools. As

mentioned in previous chapters, this approach has less to do with providing a wide range of

structured information, or attempting to adapt this information across a range of patient

contexts and a wide range of health professionals’ abilities and knowledge. A more suitable

approach might involve providing essential information to support decision-making, where the

human can more appropriately understand and deal with different contexts. Thus, the design

of systems for experts rather than expert systems, seems to be the most appropriate approach

to designing tools for medication management, both in the hospital and in the community.

7. 3.7 A technology-poor practice paradigmFrom an accredited pharmacist’s meeting about HMR software availability, the researcher

gained the strong impression that, of the six available software products, many were too

expensive, too complex or required a level of technological understanding which was beyond

the comfort level of the audience. The products included databases, Palm® applications, a

Microsoft Word ® macro tool; and a application that allowed encrypted emailing of HMR

referrals and reports. The vast majority of pharmacists were using the tools previously

described to the researcher – word processing templates in Microsoft Word® and, for a few,

Microsoft Access®-based applications.

Nevertheless, against a background of poor availability of, or inexperience with decision

support tools, field study pharmacists (and benchtop test pharmacists) were happy to ‘try

something new’ – although they appeared to be more comfortable with a process which

reflected their usual one. Therefore, when they had a choice of using the server service or a

‘local’ tool, they chose the local tool (e.g. using the digital document on a notebook computer).

This provided the best evidence of pharmacists’ discomfort with technology – the many

different ‘paths’ that resulted for the digital document during the field studies (described in Sub-

section 7.2.3.1).

Pharmacists universally agreed, however, that sharing the digital document on-line would

realise the greatest benefits. A technology environment of low IT availability and low IT

utilisation such as the one within which community pharmacists exist has been described as

having a state of ‘limited assimilation’ of IT (Bajwa et al. 2007).

GPs’ bondage to their GP desktop system had major implications for their ability to envisage

or accept anything different from their usual practice. Just as researcher considers

pharmacists to be ‘application literate’ (see Chapter 6), the GPs could be described as

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‘application bound’.

The need to better support the communication of information remains evident from these field

studies, but this requires a paradigm shift from a paper-based to a digital-based approach. A

suitable technology approach might be one which can be implemented incrementally, is

flexible in use; and complements the work flow of individuals. The document-oriented user

interaction approach used in this project is one possible way to achieve this paradigm shift.

Addressing the community health technology predicament is a matter of the right, rather than

the most sophisticated, technology.

7. 3.8 The ‘viewpoints’ of professional practice toolsThe functions and ‘viewpoints’ of prescribing and dispensing systems were initially described

in Chapter 6. To recap, the viewpoint of the GP desktop system has major implications for the

use of the digital document, as the information in the GP desktop system can only be a

snapshot of the patient when last seen by the GP, representing a prescription audit trail rather

than actual current medication use.

The desire expressed by GPs to have ‘everything’ in their system presents a challenge to the

notion of information sharing – the underlying structure of the information in the GP system

does not allow the representation a current medication record. For example, only medications

contained within the lists included in GP desktop systems can be recorded – this hampers the

ability to enter CMs and OTCs (reportedly widely used by the elderly).

Interestingly, although CMs were mentioned by pharmacists in their reports (in the

commentary field), no pharmacist entered a CM into the digital document medication lists. It

could be surmised that, as the original medication lists from the GP desktop system contained

only prescribed medications, this could be an influence on how the pharmacist reports back,

i.e. not including the CMs in with the prescribed medications.

Another influence of the GP desktop system in the referral information given to pharmacists

was the ‘pattern’ of information that was determined by the GP’s report, shown in Figure 7-12.

In this case, the GP desktop system is Medical Director®.

The digital document approach was considered the 'next step', as many GPs and pharmacists were ‘not ready for this yet’

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These reports, other than for the Home medicines review referral report, were ‘one-button’

reports which assembled patient information contained in the GP desktop system. In contrast,

the HMR review referral is based on a template containing information personalised for the GP.

This required more effort from the GP, but the pharmacist received information that was clearly

superior and more relevant to the HMR.

Of course, just because there was a heading for information in these reports did not mean that

information was conveyed under those headings. But headings did dictate what possible

information could be provided – further affected by the amount of information entered into the

GP desktop system by the GP. If information did not appear under a heading, however, the

researcher was unable to ascertain why this was so – the information might not have been

available to the GP, or the GP might simply have chosen not enter it. Referral documents could

thus vary from one extreme of a simple medication summary, to an extensive array of

information at the other extreme.

Table 7-12: GP desktop reports used to provide HMR referral information

Information type

Health summary

Sheet

Medication summary

Full summary

Limited patient history

Full patient history

Home medicines

review referral

Patient-related

Personal details, smoking and alcohol use, allergies and warnings.Social and family history.

Personal details, allergies.

Personal details, allergies and warnings.Social and family history.

Personal details, allergies.Social and family history.

Personal details, allergies.

Personal details, smoking and alcohol use, allergies. Blood pressure, weight & height (with dates)Other issues (list of vision, language, cognition etc.).Patient consent.

Medication Current &Immunisations.

Headed as ‘Medications’

Current &Immunisations.

Current Headed as ‘Medication’.

Medications and vaccinations.

Treatment Current active problems & past medical history.

nil. Past medical history.

Past medical history.

Past medical history.

Conditions / diagnosis.

Laboratory nil. nil. nil. nil. nil. nil.

Other nil. nil. nil. nil. nil. Doctor, Pharmacy & pharmacist details. Medication administrator. Reason for referral. Aids used.

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This was an interesting observation in light of the Royal Australian College of General

Practitioners' Standards for General Practice, which stipulate that patients' health summaries

are required to contain current problems, past history, allergies, medications, risk factors (e.g.

smoking); and relevant family and social history (Mara 2006). The digital document trialled in

the field studies would seem to offer both GPs and pharmacists an effective means of

complying with the RACGP standards.

GPs did not appear to place much importance on information categories – one GP put all the

illness-related information into 'medical history'. Unfortunately, as no observation of how

information was entered into the GP desktop system was possible in this field trial, the effect

of GP data entry habits remains unknown for this project.

The final issue relating to professional tools which arose during field study was the influence

of the 'business' aspects of HMRs and GP practices in general. The Medicare requirement for

an audit trail, i.e. evidence of a HMR referral, action plan etc., necessitated a 'paper trail' to be

located in one place – GP's wanted this to be within the GP desktop system. The medical

billing system was also currently incorporated into the (clinical) GP desktop system.

Consequently, GPs considered that any change in 'systems' necessitated having all this

information together in the new system. Thus, GPs' desires to have a 'single record' for both

clinical and business information created a perception that it would be too difficult for them to

change anything about their current practice.

The influence of the GP desktop viewpoint is therefore very significant for the likely success of

the system trialled in this research project, but it should not be allowed to impede progress.

While the functional role of a prescribing system will never be in question, this needs to be

acknowledged as only one role. The GP desktop system does not (in its current guise) allow

information sharing, nor does it represent a current medication record. Whether the providers

of the GP desktop systems can be involved in subsequent research is unclear, but such a

solution would obviously be ideal.

Although the digital document is seen as an additional entity, it will have to exist in its own

communication space to realise its intent of being a shareable, communicable and ultimately

current, medication record.

Pharmacists mentioned that having something ‘more universal that sat outside of Medical Director’ was ‘sensible and useful’, but also a problem.

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7. 3.9 Pharmacists’ perceptions of GPs in the HMR processThis theme first emerged in the benchtop testing phase where pharmacists perceived GPs to

be unconvinced of the value of HMRs.

The consensus of pharmacists' meetings (attended by the researcher) was also that GPs'

acceptance of and attention to HMRs was poor. This lack of conviction of the value of HMRs,

by GPs, together with their lack of time, meant that many pharmacists felt uneasy in

approaching GPs. Consequently, pharmacists were frequently unable to obtain the information

they wanted from GPs – pharmacists were especially uncomfortable in raising particular issues

e.g. had the patient been investigated for a particular condition.

During field studies, there was a great deal of variation in how individual pharmacists and GPs

approached HMRs. For some GPs, HMRs did appear to a mechanical business process –

some GPs were concerned about remuneration and the 'red tape' that came with the HMR

process. This attitude of GPs may be part of the reason, re-iterated by pharmacists, that many

GPs provided minimal information (and, for some GPs, information could still be hand-written).

All these reasons contributed to the view held by pharmacists that, while the digital document

tool had the potential to allow GPs to provide better information, it was not clear that GPs would

use it, especially in small practices.

As mentioned previously, the participating pharmacists and GPs were considered to be more

motivated than most however (possibly the reason why they chose to take part in the project

in the first place). There seems no doubt to the researcher that the better the GP-pharmacist

relationship, the better the HMR process generally. Perhaps, if the digital document can

provide an environment to improve GP-pharmacist communication and relationships more

generally, GPs' perceptions of HMRs might also improve, increasing their uptake by GPs and

potentially providing better outcomes for patients.

7. 3.10 The Practice nurseThe Practice Nurse was introduced in Section 7.3.3. Not all GP practices had a Practice Nurse

(particularly small practices) but where they existed, it became apparent that part of their role

was to be a channel for ‘direct’ communication to the GP. This was true for the researcher and

appeared to be true for many of the HMR pharmacists. Of course, where there were important

clinical issues about the patient for the pharmacist to discuss with the GP, communication

would take place directly with the GP.

Some GPs saw HMRs as 'extras'.

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However, the direct patient involvement of Practice Nurses could be substantial. In one case

the Practice Nurse carried out patient health assessments and flagged those patients requiring

medication reviews to the GP. Interestingly, one GP mentioned using receptionists to fill out

part of the medication action plan – this would require caution, as receptionists are unlikely to

have the skill or background for this role – but Practice Nurses do have these skills. Therefore,

there may be an opportunity to extend the role of the Practice Nurse to include greater

involvement in the generation of HMR referrals.

Since Practice Nurses already serve as intermediates between the GP and pharmacist; and

because of their knowledge of the patient and ability to access to patient information, Practice

Nurses are in an ideal position to generate a more complete referral document – using the

digital document. This may be one solution to GPs’ inability to use the digital document

because of time constraints (and possibly because of technology issues). This suggestion is

made by the researcher, of course, without any knowledge of the work loads which exist for

these individuals. However, as many Practice Nurses already perform health assessments,

the next step to generating a medication referral document seems logical, given the

overlapping nature of information contained in a health assessment and a HMR referral –

providing a possible way to increase the number and quality of HMRs.

7. 3.11 Complementary medicines and over-the-counter medicationCMs and OTCs were a notable omission in the information sought by pharmacists and Medical

Officers (MOs) in the hospital. During the field studies, GPs also failed to include this

information in the medication lists included in their referral documents. However, pharmacists

did note these (e.g. vitamins, topical analgesic and anti-inflammatory creams; and antacids) in

the HMR report for the GP – but still did not include them in the actual medication list.

The researcher believes that CMs and OTCs should be captured within the list used for other

(prescription) medications. This can not only contribute to the development of a complete

medication list, but existing entries can act as reminders for later visits to the GP or in other

reviews. It is arguable whether this information is always important (e.g. vitamins – although

even in this case some fat-soluble vitamins, such as Vitamin A or D, can have significant side-

effects used in high doses in long-term use), but a number of CMs (e.g. St. John's Wort), have

potentially serious interactions with prescribed medications. One reason for this omission may

be that the HMR is, at least in part, driven by the information is contained in the GP desktop

systems and how this information is expressed, i.e. only reflecting medications identified within

that system. Although the pharmacist updates the GP on the accuracy of that information, CMs

and OTCs remain a separate consideration, rather than being components of a complete

medication list. The current systems actually hinder the assimilation of this information

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Yet, as the digital document would exist 'outside' GP desktop systems – and therefore outside

their influence – it provides an ability to record this information to the advantage of the GP and

the pharmacist; and ultimately the patient, as more informed decisions can be made about

their therapy. Once again, of course, this raises the issue of how to persuade at least some

GPs of the benefit of using two quite separate patient-related desktop systems.

Attention next turns to the digital document use experiences of the pharmacists and GP,

discussed in Section 7.3.12.

7. 3.12 Field study experiences

7. 3.12.1 HMRsThe general impressions of pharmacists about the digital document were the same here as in

benchtop testing – the digital document was logical and easy to use; and became easier with

repeated use. Overall, however, time to complete a HMR report using the digital document was

longer compared to the usual practice of this group of only returning a one page (paper)

summary to the GP (because for the digital document, the HMR pharmacists were entering all

the information forwarded to them by the GP – previously, pharmacists only entered

summarised information into the word-processed reports).

Field use of the digital document led to only one change in the information model – the addition

of a ‘commentary’ field to enable an overall summary of the HMR to be conveyed to the GP.

This reflected the practice of all HMR pharmacists to produce a succinct summary – whether

they provided other information or not.

Prior to the field studies, pharmacists had suggested a need to record the (‘real’) reason for

referral. However, this could not be tested as no GPs used the digital document directly to

produce the referral. One GP did write his own referral reasons on the paper referral, but these

were still in general terms (e.g. ‘education – on multiple medication’ or ‘review of medications

and husband’s understanding’). There were no instances of a GP indicating a more specific

issue which needed to be addressed (e.g. an assessment for a dosing aid). The inclusion of

the commentary field can also be seen as a result of the absence of targeted referral reasons

– this allowed pharmacists to report back to the GP more generally (and more flexibly) in the

absence of specific reasons.

As the paper report copy of the digital document had been the main avenue for pharmacists to

report back to the GP, there was a deal of comment about this report – although comment was

largely to do with formatting (display and grouping of information) rather than with information

content. Two changes were made to the paper report during field studies:

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• The first change in the report output reflected the change made to the digital document,

i.e. the addition of the commentary element. The researcher also made this a dynamic

field, as its appearance depended on the presence of the review date – prior to the

review, this field was not displayed on the report and, consequently, was less cluttered;

but after entering the review date, the commentary text was displayed on the report. One

pharmacist did use the paper printout as a working document during the review – the

document could thus be considered to be a practical working document, being used in

different roles at different times.

• The second change was enabling the display of the calculated values for the creatinine

clearance (CCl) and body mass index (BMI) calculators – initially absent because no way

had been found to achieve this during the XSL transformation that produced the report.

Although the paper report was not a prime focus of the project, it became clear that it could

very well be used to support the current (manual) process as an interim step to realising an

more technologically sophisticated HMR setting.

7. 3.12.2 HOMRsThe general reactions of the HOMR pharmacists were very similar to those of the HMR

pharmacists – information flow within the document was logical, it was easy to use and

became easier with repeated use. The date field (not surprisingly) provided some problems.

Pharmacists commented positively about some information elements, e.g. being able to

identify who changed medication information and when – important in a hospital setting with

many health professionals. No essential information items were considered to be missing

(although existing ones were not necessarily going to be used). The 'empty slots' were seen

as a good way of eventually collecting all appropriate (and perhaps complete) information.

A major finding in this setting was that some additional hospital-related information elements

would allow the model to fit with hospital use (as well as community use).

Some suggested information elements included:

• administrative data (e.g. admission date, ward, treating team)

• details of the patient’s progress during admission

• details of correspondence during admission (between health professionals)

• a ‘comments’ element alongside medication (e.g. for monitoring requirements); and

• a separate section for ‘short-term’ medications (e.g. tapering prednisolone or antibiotic

courses).

HOMR pharmacists considered that these elements would make the digital document a

‘working document’ which could capture the flow of information within the hospital. Some of

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these additions may not be a natural fit with the intention of the information model, e.g.

correspondence details, as this is more in the direction of a complete electronic health record.

Other information elements, e.g. reasons for referral, were probably unnecessary (although

these pharmacists had used this element to record patient summaries (that could be later used

by the GP). Fundamentally, the model was a good fit and some suggested ‘variations’ in the

display of information elements in the digital document could be accommodated by different

contextual views enabled by XForms.

In summary, this opportunistic test suggested an extended use of the digital document as a

‘working document’ within the hospital environment – requiring relatively minor changes to the

information model. This working document would not only be of value within the hospital, but

could also be the vehicle for information flow into the community for HMRs (supporting the

similar paper-based process already begun in this hospital). The ability to have a digital

document that could be used within the hospital and community settings suggests a real

opportunity to improve the continuity of care for patients, at least from the perspective of

medication management.

However, as this direction differed from that of the original project aim, changes were not made

to the information model – these suggestions would more appropriately form the basis of a

future investigation.

7. 3.12.3 RMMRsMedication reviews in ACFs (i.e. RMMRs) can be seen as a hybrid of HMRs and HOMRs.

RMMRs are similar to HOMRs as information can be sought from patient records at the ACF

(although no investigation was made during this project of the degree to which problems exist

with missing or uninterpretable information in that setting). RMMRs are also similar to HMRs

in intention, i.e. this is a medication review of the patient for the GP.

The experience of using the digital document with RMMRs did not add significantly to the

findings of the field study. If anything, this simply re-enforced the notion that conciseness was

a goal for reports. Very little information contained in the RMMR reports was sent to the GP

and the pharmacist again re-iterated that the GP only needed a summary of patient issues –

rather than duplicate information which could be located at the ACF or by the GP

7. 3.12.4 The technically aware GPAs one GP (GP4) did use the digital document and was the only participant who used the on-

line service, the researcher considers this to be a significant event; and thus worthy of separate

discussion. This GP was also able to download patient files from the server to his PC on one

occasion when there was a temporary problem with digital document display on the server –

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proof of the value of providing alternative work processes.

The data provided by the GP (based on the HOT Fit model) are reported in full in Appendix

X, but are summarised here.

The GP considered the digital document to be easy to learn and data entry methods simple to

use. The information categories were considered relevant and the ability to add as much

information as required was valued.

He stated that the usefulness of the digital document for medication management was 'good',

although he would have preferred to have drugs and related issues on the same page of the

document. Although this GP regarded the digital document as easy to use, he thought 'non

computer literate people' might have some initial reservations about using it. The only

problems which required resolution, however, were some minor formatting issues.

The GP phrased the perceived gains of the digital document in terms of safety, quality,

efficiency and patient outcomes. However, some of the gains mentioned by the GP could

actually describe the gains of the HMR process itself, not just the intervention (this is a not-

infrequent result of automating any complex process – and is a phenomenon encountered by

almost all researchers investigating technology transfer and innovation diffusion). This GP was

motivated to do HMRs for the first time as a result of involvement in this project. He stated that

there were safety gains because of the pharmacist's 'excellent review' (this external audit could

detect drug interactions). He also felt that the peer review process would improve quality

assurance, but quality was also improved as the GP was 'forced' to keep records up-to-date.

Increased efficiency, though, was perceived by the GP as something that would occur once

the system was operational (rather than within this limited project – an opinion also echoed by

pharmacists).

The GP also mentioned that there had been (positive) clinical outcomes for several of his

patients (through changes to medication therapy). However, as mentioned, this could be as a

result of the overall process; and the effect of the intervention cannot be removed from the

HMR process itself. Nevertheless, the fit of the information model was substantiated for its

purpose by this especially technically literate (and technophilic) GP. The net benefits of the

intervention reported by the GP are reproduced verbatim in Table 7-13.

Information was: ‘not too much, not too little’

The digital document had ‘great potential’

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.

This concludes the discussion of data analysis. The next important considerations for this

project are: what impact did the intervention have on the medication management process?

and what, if any, were the outcomes? The evaluation of the intervention is discussed next in

Sub-section 7.3.13.

7. 3.13 Evaluation of the interventionAs planned, the tool used to evaluate the intervention was the Human-Organisation-

Technology Fit (HOT Fit) Model advocated by Yusof, Paul and Stergioulas (2006).

As there was poor use of the server service, with only one GP providing feedback, assessment

of this service can essentially only be made on the perceptions of possible use by users.

However, as the digital document was used (locally) by all pharmacists and one GP, the

information model and digital document can be assessed with reasonable confidence against

the evaluation model.

Not all the components represented in the HOT Fit model were relevant to this project. The

researcher therefore selected those which were relevant and included one further element –

quality, in the net benefits – because quality (as a broad concept) was often at the centre of

accredited pharmacists' discussions of the HMR process. The adapted HOT Fit Model is

shown in Figure 7-2 and the original model in Appendix D.

To allow easier evaluation, the researcher has separated the HOT Fit model components into

tables (Tables 7-14 to Table 7-20) which deal independently with the human, organisation,

technology and net benefit aspects of the model. The HOT Fit model and tables have also

been numbered to show the links between them. Within these tables, there is a further sub-

Table 7-13: Net benefit comments from GP4

Net benefits1. Provide seamless communication between pharmacist / doctor /patient if adequate computer skills and computer access.2. Effectively alters clinical outcomes, provides opportunity for audit & peer reviews3. Could be a source of information for ADRAC (‘adverse reactions’ body) by pharmacist alerta4. Cost effective from my viewpoint5. Link in with government payments6. Viable for me to put into practice7. A potential for other uses, e.g. doctor -> hospital, hospital -> allied health, intrahospital communication pharmacy -> medical staff, check for discharge summaries, ‘smart card - credit card for patients transferring information’8. Download laptop facility means data cold be collected at remote point and transferred at base

a. The Adverse Drug Reactions Advisory Committee (ADRAC) is the central Australian body responsible for collecting and reporting adverse drug reactions.

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division for the information model and digital document to discuss the implications for each

artefact. A more complete discussion for each item of analysis is found in Appendix X. Where

the term ‘local use’ is used in the following tables, this refers to use of the digital document with

the VB viewer on a notebook computer or PC. Server use will be referred to as such.

7. 3.13.1 Evaluation of the technology aspects of system useAnalysis against the system quality elements (Table 7-14) revealed that with local use, the

information model was flexible, based on the range of appropriate information elements,

including those which supported the use of clinical narrative (free text)

The digital document was found to be quick and easy to use and to behave reliably, apart from

the problems caused by date functionality. A positive feature was its flexibility in allowing

context-based changes in the appearance of the document, enabled by XForms dynamic

properties. The usefulness of the document was supported because of its portability to other

settings and because it acted as a template for reporting information. Security of the document

was not an issue for local use; and server use was not sufficient to ascertain whether the

security measures put in place were appropriate.

Figure 7-1: Modified Hot Fit model

2.Human

1.Technology

1b.Information Quality

DocumentLegibilityData entry methods

ModelCompletenessAccuracyRelevancy

1a.System Quality

DocumentEase of useResponse timeUsefulnessAvailabilityReliabilityFlexibilitySecurity

ModelFlexibility

2b. User satisfaction

2a. System Use

DocumentLevel of use

Resistance / reluctance

AttitudeExpectations / beliefs

Acceptance

Model

Document

Perceived usefulnessUser satisfaction

Model

StructureNatureCultureCommunication

EnvironmentPopulation servedCommunication

3.Organisation

4. Net Benefits

Direct benefitsJob effectsEfficiencyEffectivenessError reductionCommunicationClinical outcomesCostQuality

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Although system quality is clearly important for user acceptability, the researcher considers

that information quality is particularly relevant to this project, as information quality may have

an impact on the outcomes for the ultimate focus of this project – the patient.

Evaluation of the information quality (Table 7-15) supports the view that the information model

is complete and relevant for the purposes of HMR reviews. There was no opportunity to test

whether the intervention bettered the accuracy of medication-related information but this was

perceived by participants as this model (or at least its implementation) could be shared.

However, accuracy was discerned to be at least as good as for existing systems.

Improvements in legibility ascribed to the digital document resulted from the move from hand-

written reports. Data entry methods were considered simple and useable, with information flow

being logical although, once again, the date entry method was a problem.

Table 7-14: Technology aspects of the intervention – 1a. System quality

1. Technology

HOT Fit Model element Information model Digital document

1a. System qualityEase of use Easy to use, improving over time. Date

functionality caused some difficulties.

Response time Good for local use. Server response was acceptable over a broadband.

Usefulness Useful as a template for gathering, sharing and reporting information for HMRs; and as a ‘working’ document within a hospital. Usefulness also suggested in other settings. Portability suggested document use on PDA and USB devices.

Availability No problems with document operation at local use. No problems with server availability during development, testing and field access (although had limited use)

Reliability Behaved reliably throughout field use. One issue with a Microsoft security patch.

Flexibility Based on the range and nature of the information elements – free text elements allowed expression of clinical narratives too difficulty to capture otherwise. Flexibility was suggested by use in scenarios other than HMR.

XForms allowed dynamic behaviour to hide or reveal information based on context of use. Pharmacists considered the document very flexible. GP user commented that layout was not flexible (but this was not intended). Document was a useable artefact in a number of scenarios.

Security Not an issue as most use of the document use was at local level. This would be a more significant issue with a bigger group of self-enrolling users and on-line use.

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7. 3.13.2 Evaluation of the human aspects of system useOverall, the evaluation of the human aspects of system was positive (Table 7-16).

There was a positive attitude towards the use of a simplified model, although GPs’ attitudes on

what information should be contained within GP prescribing systems (compared to the

information model) affected attitudes about possible use of this tool in the future. Despite the

expectation (of GPs) that succinct information should be located in their desktop system, all

participants believed there was value in using this modelling approach to support the

communication of relevant, summarised information. However, pharmacists also believed this

‘next step’ would be difficult for GPs to take. Acceptance of this ‘essential’ information model

was good.

The digital document was viewed positively and had good use locally (for participants that

elected to use it), although there was variation on how it was used because of pharmacists’

current work practices or GPs’ wishes about patient confidentiality. The level of use of the

server-based alternative was poor. The main expectation of the digital document was that it

have some interfacing ability to the GP desktop system.

Table 7-15: Technology aspects of the intervention – 1b. Information quality

1. Technology – Information quality


1b. Information qualityCompleteness Confirmed, as only one element added to the

model during HMR field use. Pharmacists and GPs considered no essential elements were missing. Sharing the document would improve the completeness of information over time.

Accuracy No opportunity to determine information accuracy, but was considered to be as good as for use of existing systems. Sharing would improve accuracy over time.

Legibility This was considered largely in comparison to hand-written reports.

Relevancy The elements were considered logical and relevant. Relevancy of information elements was also patient-context dependant. The relevancy of alerts and reminders remains unclear.

Data entry methods Found to be simple, generally acceptable and flow was logical. A free text field for some elements was valued. Drop-down boxes were considered of limited use. Date fields could be a problem leading to inadvertent errors. Overall, data entry took longer, but not considered a major problem (by pharmacists).

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Overall acceptability of the digital document was good, with an additional benefit being that the

report, which was not a focus of the investigation, was valued in its own right. Although

pharmacists did not use the server service, they saw no acceptance issues for on-line of the

digital document.

The only reluctance encountered with the system was for on-line use (other than for one GP),

because of concern about patient privacy in some cases, or because this was too different to

the current work process. Importantly, time featured highly as an overall deterrent for any use

by GPs.

Table 7-16: Human aspects of the intervention – 2a System use

2. Human – System use


2a. System UseLevel of use Good use at local level by all pharmacists. None

used the server service. The level of use was dictated by pharmacists’ current work practices or the GPs’ wishes about patient confidentiality.Use at local and server level by one GP (time constraints prevented other GPs from use).

Attitude Positive attitude towards the use of a simplified model. How this model related to the information contained within GP prescribing systems affected attitudes about possible use in the future.

There was a positive attitude to using the digital document for those that used it.

Expectations / beliefs

GPs expected succinct information to be located in their desktop system, wanting a ‘one-button’ approach to HMRs. Despite this, they felt there was value in this approach to communicate relevant, summarised information between pharmacists and themselves.Pharmacists considered this a ‘next step’ and although desirable, questioned whether GPs would take it up.

The main expectation was for the digital document to have some interfacing ability to the GP desktop system. GPs particularly wanted the ability to produce a referral document with minimal effort.

Acceptance The model of ‘essential’ information was acceptable, having a good balance of information items. The field trial did not have any major impact on the design of the model. GPs would find it difficult to move away from current work patterns.

The digital document was acceptable in use overall. Minor changes were suggested to the layout of the document; and the paper report (although not a focus of investigation). The paper report was valued in its own right. Pharmacists saw no acceptance issues for digital document use on-line.

Resistance / reluctance

There was no reluctance to local use of the document, but some reluctance to use the server. This was concern about patient privacy in some cases, or was too different to the current work process. Time featured highly as an overall deterrent for any use by GPs.

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User satisfaction with the system in the intervention was good, as summarised in Table 7-17.

The information model was found to be useful as a basis for the communication of essential

information. Further, users felt that this approach could be useful in other settings. Pharmacists

particularly, considered that an approach which enabled information sharing ‘outside’ of the

GP desktop systems was very useful. The researcher’s general observation was that users

were satisfied with the information model.

The digital document was considered useful as a template for information gathering and

reporting, although the usefulness of alerts and reminders and calculators is unclear and

requires further investigation. There was also good user satisfaction with the document

interface (again, other than the problem with date functionality).

Evaluation of the structural components of the HMR ‘organisation’ within which the intervention

took place is summarised in Table 7-18.

The nature of the environment is one of independent, communicating professional practices

where there is no natural coordination of activities, but these rather occur on a push basis as

the patients are ‘pushed’ between health providers or services. The culture is similarly

concerned with independence – in decision-making and professional practice – with the added

complexity of being a small business environment. There is no structure in place which allows

good communication between the members of this HMR ‘organisation’; and communication

and information-sharing uses mainly a range of conventional methods (e.g. telephone and

facsimile).

Table 7-17: Human aspects of the intervention – 2b. User satisfaction

2. Human – User satisfaction


2b. User satisfactionPerceived usefulness

The usefulness of the model to support communication of essential information was upheld by users. This was reinforced by suggestions for use in other settings and applications. Pharmacists considered something ‘outside’ of the GP desktop system allowing information to be shared as desirable.

Usefulness was considered to be high, as a standard template for information gathering and reporting. The usefulness of alerts and reminders and calculators is unclear and requires further investigation. The GP that used the document considered that it had ‘great potential’.

User satisfaction The general observation was that users were satisfied with the information model – supported by the fact that users’ experiences were straightforward with few problems.

Users were satisfied with the document interface (other than the problem with date functionality). The additional time required (by pharmacists) to add data was not considered a major problem. User satisfaction of the GP was also positive.

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The implication of this structural evaluation is that this environment requires a structure to be

put into place. This structure will need to accommodate a ‘push-based’ style of communication

of information; information-sharing that allows multi-disciplinary input, but independent

decision-making; and can operate in a low technology environment. The digital document

approach advocated by this project may be an appropriate structural approach.

The environmental aspects of the HMR ‘organisation’ are evaluated in Table 7-19. The

population served in this intervention project was composed of those pharmacists and GPs

involved in HMRs in the community. However, the population which could be served by the

artefacts in this project is wider, including other health professionals involved in the patient’s

care and, of course, the patients themselves – this is the basis of some of the Future Work

described in the next chapter.

Communication emerged as the major issue in this intervention. The ability to improve

communication foresees many benefits, such as improved: information sharing between

health professionals (and across health care settings); information collection, accuracy and

use; medication-related decision-making; pharmacist-GP relationships; and ultimately better

outcomes for patients.

Table 7-18: Organisational aspects of the intervention – Structure

3. Organisation – Structure

HOT Fit Model element

StructureNature The structure of the ‘organisation’ involved can be considered a set of independent,

communicating professional practices. This is the case in the community, whether the entities are GPs, pharmacies, pharmacists, other health professionals or hospitals. There is no easy way to coordinate patient processes across these practices. It largely occurs through a ‘push’ mechanism, i.e. a health care process occurs around a patient and follows them as they are ‘pushed’ from one health care setting or provider to another, based on the outcome of the previous service. The ability to communicate medication-related information across this ‘organisation’ promises to address some of the problems of information sharing and communication inherent in its nature.

Culture The culture of health professionals in the community is one of independent decision-making, with or without input from other health professionals. As the importance and benefit of a multi-disciplinary approach gains acceptance, the value of shared information and others’ opinion is increasing. However, this is more difficult in the community (compared to the hospital), because of the poor physical proximity of health professionals; and communication issues in part resulting from perceptions about other professionals. This environment is also a small business environment that draws payment for carrying out HMRs. A communication framework suggested by the intervention may alleviate some of these issues, although a significant challenge will be alignment with, or accommodation of, business issues.

Communication There is no structure in place which facilitates good communication. Communication of HMR information occurs by mail or fax; and direct pharmacist-GP communication if it occurs, is by telephone. There is essentially no communication by email or by other on-line means. Communication of information could be easily achieved using current technology, as the digital document approach purposefully used existing standards and pursued a ‘low tech’ approach. The portability of the digital document is a major enabler of this.

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The net benefits of the intervention are listed in Table 7-20. These are a compilation of benefits

mentioned by user; and those observed by the researcher. Some of these are not easily

discerned between the information model and its instantiation as the digital document. Some

benefits mentioned by GPs would be an expected outcome of a HMR in any case, e.g.

providing an opportunity for audit and peer review. Also, some others are less specifically

concerned with the model or document, than with the nature of the (technology-based)

intervention, e.g. source of information for ADRAC or links to government payment. However,

these are all described as they were all benefits perceived by participants. Many participants

mentioned future applications or potential applications for the digital document approach –

these are discussed under future work in Chapter 8.

Table 7-19: Organisational aspects of the intervention – Environment

3. Organisation – Environment

HOT Fit Model element

EnvironmentPopulation served Although the population served in this project was GPs and community pharmacists, users saw

the potential for information sharing between other health professionals, including across the hospital-community interface. This could also include patients. The population which could be served by the digital document could be anyone that was involved in patient care that had an interest in medication management.

Communication Communication in this ‘organisation’ is a significant issue. Frequent pharmacist-GP communication is not the norm, even in the presence of missing information; and this is often compounded by professional perceptions. Good relationships with GPs were highly valued by pharmacists; and communication was much easier in these cases. The potential to improve the communication of information was the most important aspect of the intervention. This was a positive feature seen by both GPs and pharmacists. Communication could be extended to include other health professionals; and also between different communities of practice, e.g. hospital-community, intra-hospital; and with patients themselves.

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Table 7-20: Net benefits of the intervention

4. Net benefits

HOT Fit Model element Information model Digital Document

Direct benefits The information model provides a template of essential medication-related information which is to the point, relevant; and can be understood and shared by health professionals. This is the basis of many of the other benefits.

The digital document approach allows a flexible way of communicating and sharing medication-related information through a simple, easy-to-use artefact.

Job effects Simplifies the need to determine what information needs to be collected as this is suggested by the ‘template’. This can standardise expectations of what information is transferred between health professionals.

Provides opportunities for audit and peer review (although this is done by the HMR process anyway).Could be a source of information for ADRAC (through pharmacist alerting)

Efficiency The model acts as a suitable communication template to streamline the medication management process since the information structure is known to participants in the medication management process.

Timeliness and availability were seen as the main contributors to efficiency; and other benefits (e.g. safety) also flow from these.

Effectiveness Aids completeness of information collection. The digital document appeared to be an effective (and flexible) way to represent and communicate information.

Error reduction The model act as a prompt for collection of relevant information, increasing the chances of errors being detected and rectified.

Accuracy of information improves as the document is shared and updated by a number of health professionals. Encouraging the move from hand-written documents also adds to safety.

Communication Provides an expected set of information which will be communicated (although not necessarily a complete set).

Seen as a way to provide ‘seamless’ communication between pharmacist, doctor and patient (given adequate computer skills).Provides flexibility for the work process (e.g. directly on server, or patient files can be downloaded / uploaded from laptop computers).

Clinical outcomes Model will be the basis for greater clarity of information presentation (to GP) possibly increasing the uptake of recommendations.

Patient outcomes are likely to be improved if there is greater communication between health professionals. As information can be communicated more quickly, recommendations may be effected more quickly leading to better patient outcomes.

Cost No cost benefits were attributed to the information model.

It is not anticipated that direct costs of the HMR process would be decreased as a result of the intervention. However, one can surmise that a more efficient process and better outcomes could lead to cost benefits more broadly over time.

Quality Standard elements guide the depth and quality of information for reporting; and this assists Quality Assurance.

Mainly as a move from hand-written documents. But overall, this was seen as a step to generally improving the quality of reporting.

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In summary, because the intervention in the field trial was influenced by some practice issues

(as noted in Section 7.2.3), the researcher's ability to measure the effect of the intervention on

HMRs was less than perfect. Nonetheless, all pharmacists and one GP made direct use of the

digital document (locally) on a notebook computer or PC. An unexpected – but valuable –

outcome of the field study was the potential to use the digital document in a hospital discharge

setting which confirmed the flexibility of the document (and model).

The only major change to the information model which occurred as a result of the field studies

was the addition of a single information element – a free text field. These were highly valued

as they could be used to express clinical judgements, but presented a dilemma when

attempting to use categorised information as the basis for alerts. Although some data entry

issues interfered with the testing of the alert functions, they were not used by pharmacists

(although this, in itself, is a cause for some concern – as alerts in relation to drugs such as

warfarin should certainly be taken seriously). Similarly, there is no suggestion that reminders

made any difference to whether pharmacists added missing information. Whether alerts and

reminders would have made any difference to GPs' behaviour remains untested.

The digital document was generally found simple and easy-to-use; and information flow

through the document was considered logical. The requirement of the digital document for

pharmacists to add more information compared to the current word processed reports added

a little more time to the current HMR process – but was not considered a problem.

Evaluation against the modified HOT Fit model revealed benefits to the intervention: some real

and some perceived.

The fundamental benefits of the information model arise from its being a template of essential

medication-related information which is focused and relevant; and which can be understood

and shared by health professionals. This formed the basis of other perceived benefits, such as

a shared understanding of what information elements should be provided, helping with the

completeness this information, improving information quality; and improving the uptake of

recommendations (by GPs).

The fundamental benefits of the digital document are due to its flexible approach to

communicating and sharing medication-related information through a simple, easy-to-use

artefact. The document paradigm was a comfortable fit for these health professionals. Sharing

this document on-line was seen to be of particular potential value in improving the timeliness

and availability of information and communication between health professionals – contributing

to better patient outcomes.

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There were also two incidental benefits from this intervention. One GP who had not previously

undertaken HMRs was motivated to do so by this project; and a pharmacist who had previously

produced hand-written reports subsequently produced more legible reports for GPs. In the

latter case, it will be interesting to see if this improvement continues after the completion of the

project.

Issues which limited the researcher’s ability to evaluate the intervention were mainly the time

available for GPs to participate and the poor use of the server service. GPs also had the

expectation that the digital document should be interfaced with, or be part of, their GP desktop

system. This was not possible during the project – and is perhaps not appropriate, given the

different intents of the GP systems and the digital document. It was evident, however, that

there is no clear way that information communication between a number of health

professionals can be supported by the GP systems.

Nevertheless, as a proof of concept for this approach to support medication management, the

results are encouraging. Clearly, there is now a need for larger field trials to realise the full

potential of such an intervention.

The final information model which resulted from the field studies is now discussed in Section

7.4.

7.4 The information modelThe final information model which emerged after the field studies is shown in Figure 7-2. This

simply includes the additional commentary information element – the other minor re-

arrangements suggested for some of the elements have not been included as these do not

affect the model overall. Further, the dynamic components of the model – alerts and

calculators – have been retained as these should remain for future field tests. As mentioned

by the researcher, any changes suggested by the HOMR experience are issues for a future

project in a hospital environment.

The implementation aspects of the model and other functional changes resulting from the field

studies are now described in Section 7.5, with full technical details contained in Appendix Z.

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Figure 7-2: The final information model

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7.5 The digital document and the server serviceThe nature of possible changes were those which:

• were required for the document (and model) to function in the field

• were minor format changes to the document or re-arrangements to model elements

suggested near the end of the field study and were thus not implemented, or

• would take the model to different environments in future work (e.g. the hospital working

document).

Changes made are now discussed in the following sub-sections.

7. 5.1 The VB BrowserThere was no need for any changes to the existing VB browser or the (‘child’) VB Medication

Management Document Printer form during the field study.

7. 5.2 The digital documentAs mentioned earlier, the one change made to the digital document was the addition of the

additional commentary field, reflecting the addition of this element in the information model –

this change was consequently reflected in the patient XML file and the XSL report.

In keeping with having the document view reflect the context of use, the researcher made the

commentary field visible contingent on the presence of the review date. Prior to the review, the

referral page in the digital document displayed the referral date, reason for referral and

(‘empty’) review date (see Figure 7-3).

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The addition of the review date by the pharmacist (after the review) allows the commentary

field to become visible (as well as the previous information elements which became visible –

recommendations etc. – described in Chapter 6). The pharmacist could then add summary

information about the review. An example is shown in Figure 7-4.

Figure 7-3: Digital document referral page prior to review

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There were no changes to any other pages of the digital document. Changes to the XSL report

are detailed next.

7. 5.3 The XSL reportThe researcher has mentioned the two changes to the XSL report earlier in the chapter. The

first change reflected the addition of the commentary field to the referral page on the digital

document. The second change was the ability to perform Body Mass Index (BMI) and

Creatinine Clearance (CCl) calculations during the XSL transformation of the patient XML file

into HTML output.

As a paper copy of the XSL report could be taken to the review as a working document, it was

important for it to carry only the referral information and not be cluttered by other detail e.g. an

‘empty’ commentary field. Prior to the review, the XSL report was that shown in Figure 7-5.

Figure 7-4: Digital document referral page after review

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Once the pharmacist entered the review date into the digital document, this act triggered the

ability to display the commentary information on the report; and output ‘signature’ alongside

which the pharmacist could sign their name (once printed on paper) (Figure 7-6). As this

commentary was the main summary of the HMR produced by the pharmacist for the GP, it was

important that it captured the attention of the GP. The researcher thus chose to output this

information at the top of the report, immediately under the dates – this ensured that the GP

saw the summary of the HMR before other information. With the ability to display (or not) the

commentary information the paper document could function as both a working review

document for the pharmacist and a report for the GP.

Figure 7-5: HTML output of document before the HMR review

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The second change was the ability to display calculated values of the BMI and CCl in the

report. Initially, the researcher had not found a way of calculating values during an XSL

transformation of the patient XML file. BMI and CCl were calculated in the digital document and

could be manually transferred onto the paper report by the pharmacist – this was not ideal. The

solution to the calculation problem was through the use of embedded VBScript functions in the

XSL file.

An example of these calculated values on a section of a report is highlighted in Figure 7-7.

Figure 7-6: HTML output of document after review

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Figure 7-7: HTML report output – calculated values

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7. 5.4 The server serviceThe server service was not changed other then the need to update the XSL file (for consistency

with the VB browser).

Two errors were encountered by the GP who used the server service: the first of these was

that a complete list of his patients did not appear on the server. On investigation, the patients

were there and viewable by the researcher, so it was not clear why this information had not

appeared on the GP's first log-in.

The second error was an inability to open some patient files. Investigation by the researcher

revealed that this problem was resulted from a parsing error with the naming convention used

for the patient XML file – due to the presence of a comma (,), e.g. lastname,firstname.xml. This

problem had not occurred when using the VB browser, as the VB code was able to deal with

the presence of commas when parsing the filename (text). The server problem was resolved

by changing the file name format to lastname-firstname.xml format.

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7.6 Chapter Summary This chapter has reported the field study interventions which sought to evaluate the information

model and digital document prototype in operation in the medication management community,

prepared for this context by prior benchtop testing by accredited pharmacists. The chapter now

concludes by addressing the three research questions posed at the beginning of the field

study. This is done consecutively under each question heading below.


As a proof of concept, the intervention was sufficient to perceive benefits for the medication

management process, health professionals and patients.

Contribution to safety was likely to arise through prompting pharmacists and GPs for

medication-related information which is relevant to decision-making. Relevant information

increases the chance that pharmacists and GPs will be able to detect and correct errors. As

the document would be used and updated by health professionals over a period of time, this

revision of the document would also improve the accuracy of the information contained within

the document. The ability to share information in a more timely manner, together with better

information availability (particularly for the GP) means that recommendations about patients'

medication could be effected more quickly; and thus lead to better patient outcomes. Where

use of the digital document encouraged moving from hand-written reports, gains in legibility

were also likely to contribute to patient safety. Nevertheless, although safety gains were

perceived, this would need to be confirmed through more extensive field studies.

Quality was examined under system and information headings using modified HOT Fit model.

Although system quality is important for usability and acceptance, the researcher considers

that it is information quality, or rather the impact of information quality which is of most

relevance to this project. Quality was a persistent issue in accredited pharmacists’ meetings –

for the HMR process itself and the HMR report. The ideal suggested by pharmacists was: to

have adequate, relevant information to review the patient; to be able to communicate a

succinct summary of the essential issues to the GP in a timely manner; and to receive GP

feedback though a medication action plan. The digital document approach provides a possible

solution for this ideal. In addition, promoting the use of standard (and essential) information

elements can guide the depth and quality of information required for reporting. The move away

from hand-written reports certainly adds to quality overall.

Efficiency gains in the HMR process were envisaged by participants through the ability to

convey the information electronically – again improving the timeliness and availability of

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information. Not only could this allow patient-related decisions to be made more quickly, but

also could facilitate feedback to the pharmacist – currently an uncommon event.


The contribution of the model is to provide a template of essential medication-related

information which is succinct, relevant and can be understood and shared by health

professionals. This contribution is reinforced by the digital document’s ability to be used in

different medication management scenarios. Thus, the principle contribution is a relevant

framework for medication management-related information.


The contribution of the digital document is to allow a flexible means of communicating and

sharing medication-related information through a simple, easy-to-use artefact. Although the

information model could be implemented with other approaches, the document-centric

approach was a comfortable fit with health professionals’ practice. The advantage of being

able to use the document in a number of ways in the project (on-line or ‘locally’) demonstrated

its flexibility in different work flows. The ability to provide some dynamic functionality in the

digital document, still offers potentially useful (although probably limited) application. In brief,

the principle contribution of the digital document is its natural fit with the work environment; and

it’s flexibility in use and communication.

This chapter concludes the analysis and discussion of the field studies, the last of the three

iterations which developed, tested and evaluated the artefacts of interest in this project – the

information model and digital document.

The next and final chapter, Chapter 8, collects and addresses all the research questions

posed in this project. It also considers themes and coincidental findings which emerged during

the project; and reflects on the contributions of the project. Finally, it will discuss future work

realised by the researcher or suggested by project participants.

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Chapter 8

Summary and conclusions

8.1 IntroductionChapter 7 described the third and last investigation scenario of this project, the field studies

that evaluated the artefacts of interest – the information model and digital document. In

particular, these artefacts were evaluated for their ability to support medication reviews

undertaken by community pharmacists and General Practitioners (GPs), the impact on the

medication review process; and any implications for patient outcomes.

In this, the final chapter of the thesis, the researcher summarises the project, brings together

the main conclusions drawn from the research findings, provides answers to the research

questions; and suggests avenues for further research.


• a summary of the project is given in Section 8.2

• the themes that emerged during the project and directed the development of the

information model and digital document are summarised and discussed in Section 8.3

• a summary of the changes to the information model which occurred through the different

research scenarios is presented in Section 8.4

• the research questions are brought together and answered in Section 8.5

• Section 8.6 summarises contribution of the research to theory and practice; and

• the chapter concludes by suggesting future work in Section 8.7.

8.2 Project summaryThis project explored whether a technology tool could be used to improve medication

management from a patient-focused perspective. Pharmacists were the main target of this

project as they have an important and evolving role in medication management, specifically in

medication reviews. The project had the potential to improve safety, quality and efficiency in

the medication review process for patients and more generally, to consider influences which

might have an impact on the development and uptake of technology tools in the medication

management environment. Some of the project findings also have broader implications for how

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technology tools are taken up within the Health sector; and for the consequent effect on

outcomes for health consumers.

In the absence of existing and relevant information models for medication management, the

researcher developed such a model himself by means of an investigation of information needs

and work flow. A document-based approach was chosen as the implementing solution for this

model, because documents are the prevailing information-sharing paradigm in Health. This

was a natural way to communicate and support clinical documentation for health professionals;

and the solution could readily be implemented as a digital document, using XForms – an XML-

based, next-generation markup language with promise for modelling human-computer

interactions and decision support, based on a document metaphor.

The information model and digital document evolved in parallel during the investigation of three

different use cases. In the first iteration, the information model and, subsequently, the digital

document prototype, were developed in the information-rich hospital scenario with clinical

pharmacists and medical officers. The second iteration prepared the information model and

digital document for the community context by testing by pharmacists accredited to undertake

Home Medication Reviews (HMRs). The third and final iteration tested these artefacts by

means of an intervention in the community medication review environment, where pharmacists

and GPs jointly undertook the medication reviews. The researcher then evaluated the

community intervention to assess its contribution to quality, safety; and efficiency, on the

medication review process.

The Design Research loops consisted of: data collection and analysis, reflection, modelling;

and prototyping – enabling the information model and document to evolve within the context

of supporting pharmacy decision-making and, as is normal with Design Research, feeding the

each iteration's findings into the planning for the next. Data triangulation was also used in these

scenarios to address the validity of both the data gathering, as well as the approach taken.

Before addressing the research questions specifically, it is appropriate to reflect on the themes

which emerged during the project. These were not only important as a framework within which

the researcher analysed and discussed findings, but also because they had direct implications

for the approach taken to developing the artefacts; and because they also have possible

implications for the adoption of technology tools by health professionals more generally. These

themes are discussed next in Section 8.3.

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8.3 ThemesAll the themes identified had implications for the design of the digital prototype – but one theme

was of particular professional interest to the researcher (himself a pharmacist).

Complementary and over-the-counter medications were not a specific target of investigation,

but were shown to be important for patient care. It became clear that these additions to patient

medication were not covered by existing methods of undertaking community medication

reviews, although these medications have significant potential implications for patients' health.

The electronic document recommended by this research project does, by contrast, enable the

inclusion of this group of self-recommended medications – and thus provides community

health care professionals with the ability to ensure a more thorough (and consequently safer)

understanding of patients' existing medication.

Other themes identified during the empirical research, such as the role of the practice nurse,

provide the potential for future work. The themes have been grouped under two headings: the

hospital and the community (as benchtop testing and field studies were both community

settings). The full set of themes is shown in Figure 8-1; and discussed in the subsequent sub-

sections, beginning with Sub-section 8.3.1. The implications of these themes are summarised

in Table 8-1.

Figure 8-1: Project themes

Hospital

CommunityMissing information

Conversation & communication

Information granularity & the language of health professionals

Time constraints & summary information

Decision support tools

Alerts and reminders

Systems for experts

Complementary &

over-the-counter medications

Perceptions about GPs

Technology-poor practice paradigm

Viewpoints of professional practice tools

The role of the Practice Nurse

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8. 3.1 Missing informationThe widespread problem of missing information evident in the literature was confirmed

immediately in the hospital scenario. The most common – and of most consequence to this

project – was that of medication-related information (and its lack). Missing information was also

a significant problem identified by community pharmacists during benchtop testing; and this

fact was confirmed during field tests.

The problem of missing information was more critical for HMR pharmacists than for hospital

pharmacists, as they had fewer information sources on which they could rely. Field studies

observed that a broad range of information could be missing; although an immediate impact

on the patient was less likely in the community than in a hospital, because the focus of care in

the community was on chronic disease management, rather than on acute situations as in

hospital. In other words, patients in hospital are generally much sicker than those being treated

in the community, so that missing or inaccurate information relating to their medication is likely

to have a much more serious effect.

Pharmacists could obtain information during patient interviews, but this ability was limited in

both hospital and community scenarios, because patients were not always reliable sources of

information. Although hospital pharmacists were able to elicit some missing information from

other health professionals, HMR pharmacists had only themselves to rely on and would often

press on with a medication review despite a lack of information; merely suggesting to the GP

that the HMR could be of limited value.

Other aspects of missing information were seen in the community: predominantly 'pattern'-

based missing information, founded on the patient reports from GP desktop systems provided

to the HMR pharmacist as the basis for the referral.

The most significant importance of missing information is its profound effect on the

effectiveness of decision support systems, which cannot function in the absence of relevant

information, e.g. the inability to calculate a dose in the absence of a patient weight value or

making prescribing recommendations in the absence of a coded patient diagnosis. Until this

problem can be resolved, one way forward may be to allow a decision support system to

operate with missing information, but to signal caution or limit recommendations; and to

highlight the need for clinical judgement. This approach would also have less impact on the

work process of health professionals.

From the point of view of this project, missing information became important as a basis for

formulating the initial information model. Whether hospital pharmacists pursued missing

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information for their decision-making was dependent on the importance of that information to

their decision. The researcher therefore concluded that a decision to pursue an information

element actively could be used as a surrogate for the value of that information element to the

decision-making process – and, consequently, as a surrogate for inclusion into the information

model. Further, because the digital document (the implementation of the model) is

communicated and shared among health professionals, the decision to identify sought

information elements consequently provides an opportunity to collect these missing elements

and thus provide a more complete, possibly current, record of medication use.

8. 3.2 Information granularityOne important aspect of information for both doctors and pharmacists was the varying levels

of granularity of information elements, which became evident both during the formulation of

requirements for information modelling, as well as during the analysis of missing information.

In the hospital environment, the nature of information ranged from patient case-notes to

specific data items such as a laboratory value, i.e. from aggregate to atomic levels of

information. The level of the information sought was driven by the need of the health

professional, for example, whether they knew little about the current situation and required

aggregated information such as a patient's case notes; or whether a pharmacist simply needed

a specific data item on which to base a decision. Participants mentioned during interviews that

they wanted 'everything' but conceded that a more useful day-to-day form of information would

be a concise summary, representative of important issues for the patient.

The changes to the hospital-based information model for the community context also

confirmed the need for elements at different levels of granularity – additions included

aggregated items (e.g. a field for patient indications) as well as atomic elements (e.g. a serum

creatinine value). It appeared that community pharmacists and GPs had a greater need for

aggregate data items than was the case in hospital scenario. The researcher considers the

granularity of information has two implications for information in clinical systems:

representation and communication.

Representation: there is enormous difficulty in providing all patient data at an atomic level

suitable for patient-centric decision support (attested by the vast efforts in producing

taxonomies and terminologies on which to build decision support systems). By contrast, the

clinical narratives (which include acronyms and 'shorthand'), used and valued by pharmacists

and GPs, do not readily underpin decision support. This represents a tension for the design of

health information systems – the need for atomic data to develop shared terminologies and

ontologies on which to build decision support systems and allow epidemiological research, vs.

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the need to share contextual information for patient care. The reporting of information needs

at different levels of granularity suggested that the information model and, consequently, the

decision support tool, should also reflect this granularity. Passages of text present particular

problems. How can structured lists (in decision support tools) be used to compose meaningful

(and readable) clinical narrative?

The information exchanged between these health professionals requires additional knowledge

– the patient context – to make it meaningful. Meaning occurs now because health

professionals make use of their shared and understood 'language'. It is expected that any

structure imposed by decision support tools on these 'conversations' will be met with

resistance from health professionals. Thus, the information communicated by the digital

document should be in the everyday language of practice of health professionals.

Communication: the information communicated between health care professionals should

occur in a way which complements their work processes and information flows. This project

identified simplicity and flexibility as important aspects of information communication between

pharmacists and doctors. The issue is, once again, how aggregate information can be

communicated between systems to allow humans to retain and share the rich narrative that is

meaningful to them – while simultaneously supporting the categorisation of the information

needed for 'seamless' inter-connectivity?

8. 3.3 Conversation and communicationConversation was revealed as a very important information pathway for hospital pharmacists:

primarily to chase missing information, but also as an efficient way of obtaining contextual

information about the patient, even when other sources were available. There are also many

occasions when tacit knowledge held by other health professionals would not otherwise be

available to the pharmacist. Conversation has other important roles, e.g. social roles, or

opportunistic interventions for education of other health professionals; and these cannot be

usurped by decision support tools.

HMR pharmacists' conversation opportunities were essentially limited to the GP, although field

studies observed the Practice Nurse as a 'front-line' to GPs. Although conversations with GPs

occurred infrequently – even when information was missing – pharmacists valued good

relationships with GPs. The importance of good communication was also supported by the fact

that pharmacists believed the digital document could provide common ground between

pharmacists and GPs to assist communication – and perhaps even improve relationships.

The use of conversation as a significant means of communicating information has a number

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of implications for decision support tools. Firstly, it is unlikely that all the information required

for decision-making will be captured for any decision support system – much of the

communicated information is the tacit knowledge of other health professionals. Secondly,

information about a patient will be summarised and can be highly contextual to the decision-

making process – this is a very efficient way of transferring information; and is the reason why

pharmacists often used conversation as their first information-gathering option. Thirdly,

conversation plays other social roles which can not be directly supported by decision support

tools.

It is clear that decision support tools can only in part support the information needs of health

professionals. The 'conversations' between health professionals must be supported, alongside

other means of communication, by decision support tools.

8. 3.4 Time constraints and summary informationTime, or the lack of time, was a constant influence on the health care process

In hospitals, the time to find, assimilate and interpret information was a significant issue for

pharmacists; and even more so for MOs. The need to cope with many patients and press on

with ward rounds was a major deterrent to MOs' interaction with decision support systems.

Despite pharmacists' and MOs' desire to have all patient-related information available to aid in

their decision-making, the concept of an artefact with summarised, relevant, patient-related

information was seen as a practical solution. Participants acknowledged that a trade-off

between displaying essential and all information would be difficult to achieve.

In the community, time was mainly an issue for GPs, affecting the quality of the HMR referral

sent to the pharmacist; as well as their ability to deal with HMR reports sent back to them by

pharmacists. Time also adversely affected GPs' level of involvement in the project. Many GPs

wanted a 'one-button' approach to generating HMR referrals; and expected reports from

pharmacists to be short and to the point. Pharmacists' awareness of these issues meant that

they strived to produce summarised reports which would minimise the time impact and

maximise report impact on GPs.

The impact of time, therefore, was on 'shaping' the information required or produced by health

professionals. This information shape always took the form of high-level information

summaries which could be considered quickly.

In the community setting, therefore, unless there is a significant change to the time available

to GPs, or the nature of the HMR process, GPs' enthusiasm for HMRs is likely to remain low.

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Thus, even with the possibility of providing information in the correct shape, any technology

must realise a balance between the information quality required for safe patient care and the

expediency required for business efficiency.

8. 3.5 Alerts and remindersAlerts and reminders are generally held to be practical and useful components of decision

support tools. Certainly, within the hospital setting, alerts and reminders were seen as the most

positive features of a decision support system – an avenue to promote good prescribing

practice. However, the value of alerts and reminders to decision-making was qualified by their

ability to perform within an appropriate patient context – but tailoring alerts for each drug,

disease and patient possibility is difficult. Alerts were considered to be of value in areas relating

to toxicity (e.g. previous ADRs for a patient); in unfamiliar areas (e.g. drug contraindications in

pregnancy); or in the case of issues requiring immediate attention. However, even these

serious reminders would become a nuisance if they occurred too often; and the threshold at

which they became an irritation could (and probably would) vary for each individual doctor.

Even if alerts were supported by reference information (as to why they were important), it was

their relevance which was the most important issue for acceptance by health professionals.

The introduction of reference information, however, would obviously introduce an extra level

of reading and inconvenience, limiting its usefulness. The possibility of personalising such a

system, so that more experienced MOs could control the number and frequency of alerts, was

not discussed by participants and should form the subject of future research.

Although the concept of alerts and reminders was supported in the hospital setting, this was

not the case in the community. HMR pharmacists suggested that alerts and reminders

provided in the digital document would be of limited use; and this view was confirmed during

the field studies, where it became apparent that the information required to trigger alerts was

often missing in the digital document – either because it had not been included in the original

HMR referral from the GP, or because the pharmacist did not act to the alert (by entering the

missing information).

In summary, the researcher believes that alerts and reminders pose a quandary for decision

support tools. With the ever-increasing amount of information available, the inclusion of alerts

and reminders in the 'background' of such a system to assist health professionals in recalling

crucial issues is intuitively desirable. For alerts and reminders to be truly useful, however, they

must also capture and structure information so that it is relevant to decision-making in both

hospitals and the community.

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A further issue in the community setting is that current information management practices by

pharmacists did not permit the evaluation of alerts and reminders in this project – so that the

usefulness of even the simple alerts and reminders implemented in the digital document

remains unclear. Clearly, this issue needs to be confirmed by larger and better controlled

studies.

8. 3.6 Decision support toolsAll hospital participants had exposure to decision support tools, although many of these were

simple information retrieval or laboratory reporting systems, reflecting day-to-day activities. In

addition to having more experience or exposure in this area, pharmacists offered more

opinions, particularly relating to the lack of success or usefulness of the systems they had

encountered – hampered by poor training or understanding of how the systems functioned.

HMR pharmacists' experience with decision support tools also reflected their work

environment: the availability of technology-based tools in the community was significantly less

than in the hospital setting, with HMR pharmacists being exposed only to a small range of

paper-based and electronic drug information resources. The only support for the HMR role was

a word processor! Interestingly, pharmacists in both settings failed to distinguish between

technology-based and other sources of decision support – whether paper-based, telephone-

based, or interaction with other health professionals.

What information a decision support system should provide – and whether this would be

possible – were areas of much discussion. In the hospital, many MOs and pharmacists saw

patient summaries as useful output from a decision support system, with the added ability of

the decision support system to allow links to more detailed patient information; although they

also believed that all information should be presented, on the basis that it was better to discern

the value of the information for oneself, than to allow a system designer or programmer to

make that decision. This difficulty of requirements engineering – ensuring that a subsequent

system will truly reflect the needs of its users – becomes still more complex when there are a

variety of users, with differing needs. It was not surprising to find a considerable level of

concern about the effectiveness of decision support systems in an acute care setting.

Participants also noted that the availability of wider information depended on 'someone' to

enter it; that reliance on such systems could present other problems; and that it was possible

for information to be incorrect, e.g. a diagnosis could often be incomplete, being a 'work in

progress' for the first few days of admission. How can decision-making be supported against

a background of varied and changing information?

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While expressing opinions about 'ideal' decision support, participants offered a wide range of

interpretations of decision support, with many views about information integration, mentions of

prompts and alerts and discussions of evidence-based information. The researcher believes

that, because participants' perceptions of the nature of a decision are generally based on their

(less than ideal) experiences, it is hardly surprising that clinicians, when asked what they want

from a decision support system, find it difficult to express their requirements succinctly and

clearly.

Hospital pharmacists' ability to access the same information as MOs was viewed positively

because this was seen as important for patient safety – viewing the same information through

'different eyes'.

It seems logical that the approach to designing decision support systems should take note of

the requirements of different user groups, e.g. pharmacists and MOs. However, there are a

number of problems to be solved:

• the conflicting requirements, not only between user groups, but within those groups

• the difficulty of incorporating all the required information to represent patient contexts

• the problem of structuring information to accommodate a variety of purposes.

Even when these problems are solved, there is still no assurance that data in the system will

be correct. Perhaps one solution would be to maintain the status quo – allow health

professionals to continue to share the same information, but assist them to do so by means of

technology. This not only allows simplicity of design for decision support systems, but also

continues to enable the 'different eyes' to contribute to patient safety. What does remain clear,

however, is the opportunity in these hospitals to develop more sophisticated decision support

for both pharmacists and MOs.

The situation in the community was different, in that HMR pharmacists' day-to-day experience

of decision support tools was far less than that of their hospital colleagues. In part, as this HMR

group was far less sophisticated in their technology use in general, there were fewer clues

available to the researcher about decision support needs. The main finding was an insight

about where a decision support tool might fit within the HMR process – before or after the

HMR. However, the more significant effort in the community is likely to be about enabling

information sharing through decision support, rather than prospective discussions about how

it should be shared.

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8. 3.7 Systems for experts rather than expert systemsMuch of the decision support discussion which arose in hospitals (particularly that relating to

electronic prescribing) was very much in the spirit of expert systems. The researcher has

already described the problems of capturing and structuring knowledge to allow a complete

representation of a patient in an information system.

A further factor to consider is the extensive use of personal (tacit) knowledge by health

professionals in their clinical practice. This thesis made no attempt to quantify such use, but

statements from pharmacists indicated the extensive use of personal knowledge – this was the

first strategy in responding to a question. Within the hospital environment, gaining this

knowledge took many years, fed by a range of formal sources and informal sources. Clinical

practice and personal experience were particularly significant. Over time, pharmacists' recall

of previous situations became the knowledge base for approaching new problems.

Pharmacists' understanding of the 'systems' outside the hospital environment also allowed

them to consider patient care more broadly than simply in terms of immediate medication use

within the hospital admission.

One knowledge-based approach to information gathering by pharmacists was to infer which

medications a patient should be taking on the basis of that patient's diagnosis – the absence

of a particular medication in the patient's list could indicate a possible omission in the current

medication list, or a need for the pharmacist to recommend a therapy option to the patient's

doctor. This, of course, is a role which could be undertaken by a decision support system –

but, once again, this presumes a large amount of accurate, contextual clinical information and

is an outcome which might well be unacceptable to both MOs and pharmacists.

Within the hospital, the knowledge level and experience of the pharmacists made them

'specialist' practitioners – some approached as consultants in their areas of practice, both from

inside and outside the pharmacy.

Just as clinical pharmacists in hospitals evolved into 'specialists' so, too, did HMR pharmacists

evolve within the community setting. This is evidenced prima facie by the requirement to

undertake further training for accreditation. But, in the presence of even less information

available for medication reviews (compared to the hospital), the reliance on use of personal

knowledge was very high.

The researcher believes that the enormous difficulty of capturing knowledge for a decision

support system and the extensive use of personal knowledge across the continuum of

medication management suggests a particular approach to the design of a decision support

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tool: the idea of designing 'systems for experts', rather than expert systems. This approach has

less to do with providing a wide range of information and attempting to adapt this information

across a range of patient and user contexts, than with providing essential information to

support decision-making, where a human can more appropriately understand and deal with

differing contexts.

8. 3.8 A technology-poor practice paradigmThe paucity of technology use in the HMR environment throws up a paradox.

Pharmacists have used (computerised) dispensing systems for many years and many have

experience of computer-based information tools – they could be seen both by health

professionals and others as quite 'experienced' in the use of IT, i.e. 'IT-literate'. Yet the

shortage of tools to support medication management has been confirmed by the researcher in

this scenario. All pharmacists were using 'simple' technology support, e.g. mainly word

processing tools for HMR reporting. There was very little (if any) use of technology-based

communication tools, e.g. email or web-based tools – paper-based information sources

prevailed. In light of these observations, the researcher considers that pharmacists should be

considered 'application-literate' rather than 'computer-literate' (as, indeed, would many health

professionals). Nevertheless, pharmacists were not adverse to trialling the digital document.

In fact, they were happy to 'try something new', but were more comfortable with a process

which reflected their usual one. When they had a choice of using the server service or a local

tool, therefore, they chose the latter. Although they were 'not ready for this yet', the researcher

gained the impression that simple, useful tools to help with HMRs would be welcomed.

Bondage to the GP desktop system had major implications for GPs' ability to envisage or

accept anything outside this desktop system. As the pharmacists have been described as

'application literate', the researcher considers the GPs to be 'application bound'.

There are two main issues arising from this technology-poor practice paradigm. Firstly, there

is a need for some technology to better support communication. Secondly, the ability to use

any technology-based tools will require a paradigm shift in community pharmacy practice.

From the perspective of this project, the shift required is that from communicating paper-based

information to communicating digital information. A possible way forward would be to use an

approach which can be implemented incrementally; is flexible in use; and complements the

work flow of individuals. The document-oriented user interaction approach trialled in this

project may be a way to achieve this goal. Addressing this predicament is a matter of the right

technology, not of more sophisticated technology.

8. 3.9 The ‘viewpoints’ of professional practice toolsGPs expressed the view that an interface to, or interaction with, the GP desktop system was

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needed for the digital document. This desire was to some extent mirrored by pharmacists, who

believed GPs would not use two separate systems. Further, there were some early

suggestions by pharmacists that the digital document could incorporate some features of

existing prescribing and dispensing systems: primarily drop-down lists.

The project, however, has no intention of duplicating features of these systems, as they serve

entirely specific and different purposes. The researcher takes the view that prescribing

systems and dispensing systems are built around the supply of medications. Prescribing is

concerned with the intention to supply a medication to a patient; and dispensing with the actual

supply of medication to a patient. However, neither can lay claim to representing what the

patient is actually taking – although this can be the belief of some GPs and pharmacists.

In relation to representing broader medication use, the prescribing system encountered in the

project had some limited ability to record Complementary Medicines (CMs) and Over-the-

Counter (OTC) medications taken by the patient, if this medication was included by the GP. A

CM or OTC, however, cannot be recorded in a dispensing system by the pharmacist. The only

way to reveal what actual medication the patient is taking is though a medication review.

The digital document used in this project has the potential to record all medication used by a

patient – it can become the 'current medication record', based on its ability be shared by the

relevant health professionals (and, ultimately, the patient). GPs' desire to have 'everything'

included in the GP desktop system presents a major impasse. Not only are the viewpoints of

the digital document and the GP desktop system different, the underlying data structures of

these proprietary systems are unlikely to exist in a form which allows the representation of a

current medication record. The researcher's own experience suggests that the proprietary

nature of many GP desktop systems makes even simple data interchange difficult.

The influence of the GP desktop viewpoint is therefore significant. But it should not impair

progress. While the functional role of a prescribing system will never be in question, it needs

to be acknowledged that it has one role only. The GP desktop system does not (in its current

guise) allow information sharing, nor does it represent a current medication record. Although

the digital document may be seen as an additional entity, it will need to exist in its own

communication space to be a shareable, communicable and, ultimately, current medication

record.

A further influence of the GP desktop system on the referral information given to pharmacists

was the 'pattern' of information determined by the report used by the GP. This pattern was the

result of the different information headings in the reports. These headings dictated what

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possible information could be provided to the pharmacist – although there was no certainty that

this information was provided. The variability of the information under these headings was

likely to be due to the data entry habits of GPs into the GP desktop systems, although the effect

of GP data entry habits was not studied during this project – this is another area of future

research.

8. 3.10 Complementary and Over-the-Counter medicationAlthough the researcher has mentioned that CMs and OTCs were not specifically targeted by

the project, they were notable omissions from the information sought by pharmacists and

medical officers in hospitals. Patients seldom considered or brought in CMs and OTCs when

they came in to hospital – but, in any case, CMs and OTCs were not included in the routine

questioning of patients about their medications by MOs or pharmacists. Against a background

of increasing consumer self-medication with CMs and OTCs, this appears surprising, as well

as being disappointing, considering that there is increasing discussion in the medical literature

about potential interactions of CMs with prescribed medications. It appears a 'blind eye' was

turned to CMs, except perhaps where they came to mind in particular clinical scenarios.

There was a greater awareness of CMs and OTCs by community pharmacists carrying out

medication reviews, who often reported their use back to the GP in HMR summaries (although

they were not included in the digital document medication list).

It is, of course, debatable whether recording information about CMs and OTCs is always

important (e.g. for vitamins), but it will be important for some medications where there are

potential interactions with prescribed medications (e.g. St. John's Wort). However, for CMs

and OTCs to be part of an ongoing medication record, they should be captured in the list of

other (prescription) medications. Their inclusion not only aids in obtaining a complete

medication list, but also serves as a reminder to ask the patient about CM and OTC use in later

visits to the GP, or for other medication reviews. This ability could also extend to the hospital

setting, if the digital document became more broadly shared.

Because the collection of information for HMR referrals is driven by the type of information

contained in the GP desktop systems, CM and OTC information is rarely collected. That is, as

the GP desktop system only contains information about prescription medication, the 'prompt'

for the pharmacist is only for prescription medication to be updated within the GP system. So

when the pharmacist updates the accuracy of the 'GP's list', CMs and OTCs will be reported

separately; and the GP's medication list will remain a separate, incomplete medication list.

The researcher's belief that the digital document should exist 'outside' GP systems (and,

therefore, outside their influence), is based on the observation that these systems have

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different viewpoints; and that independence is required to allow the communication of

information between health professionals. This independence also now provides an

opportunity to record information about CMs and OTCs to the advantage of the GP and the

pharmacist and, ultimately, the patient to enable informed decisions about therapy.

8. 3.11 Pharmacists’ perceptions of GPs in the HMR processFollowing the hospital scenario, the researcher concluded that pharmacists had no hesitation

in communicating with medical officers (or any other health professionals) to seek information,

or for any other purpose. However, for community pharmacists, communication with GPs was

infrequent and often undertaken reluctantly. This reluctance by pharmacists was expressed in

accredited pharmacists' meetings, benchtop testing and field studies. There was a uniform

understanding by pharmacists that GPs were busy; and that they should not be bothered

inappropriately. However, there was also a perception that many GPs were not convinced of

the value of the HMR process – suggested by pharmacists as a reason for the poor uptake of

HMRs by GPs. Other GPs appeared to approach HMRs as a mechanical business process –

reinforced by pharmacists' experience of poor, or no, feedback from GPs after HMRs. Not only

is this situation unfortunate, but it has potential implications for patient safety, evidenced by

pharmacists being unaware of the outcomes of HMRs for patients.

Where good GP-pharmacist communication existed, this was highly valued by pharmacists.

For the field study group, relationships between GPs and pharmacists were good, but this

study group was atypical, being unusually motivated about HMRs compared with the norm.

The researcher feels no doubt, however, that the better the GP-pharmacist relationship, the

better the HMR process generally.

This has two possible implications for the digital document. Firstly, as an intervention tool, the

digital document may initially be more successful where good relationships (and

communication) already exist – the intervention will be seen as an avenue to improve the HMR

process. Secondly, using the digital document may itself provide an environment which not

only helps communication, but also could improve relationships – by providing a focus for HMR

improvement and 'forcing' communication. This latter point was implied by pharmacists in the

benchtop and field study groups. And where good communication exits so, too, might there be

better outcomes for patients.

8. 3.12 The role of the Practice NurseNot all GP practices have a Practice Nurse, especially small GP practices. During the project,

it was evident to the researcher that the Practice Nurse was often the channel for 'direct'

communication with the GP. This was true for the researcher; and appeared true for many of

the pharmacists undertaking HMRs. The pharmacist, of course, would still discuss important

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clinical issues with the GP. The direct patient involvement of a Practice Nurse is often

substantial, e.g. carrying out patient health assessments and flagging patients who require

medication reviews to the GP.

There is an opportunity here to extend the role of the Practice Nurse to include more direct

involvement in the generation of the HMR referral, as time was a major deterrent to digital

document use for GPs. Interestingly, one GP mentioned using receptionists to enter data into

a Medication Action plan – an area of some concern, as receptionists are unlikely to have the

skill or background for this role. Practice Nurses, however, do have both the school and the

background for this task. As Practice Nurses are an intermediary between the GP and

pharmacist, have knowledge of the patient; and have access to patient information, they are

in an ideal position to generate a referral document i.e. using the digital document. The

researcher makes this statement without knowledge of work loads for these individuals – but,

as many Practice Nurses perform health assessments, the creation of a medication referral

document seems a logical next step, given the overlapping natures of these documents. In

light of the issues of time and GP desktop system interfaces, extending the role of the Practice

Nurse provides a possible way of increasing the number and quality of HMRs.

Reflection on the themes which emerged during the project now concludes with a summary of

the themes presented in Table 8-1, in which the themes are considered within and across the

hospital and community settings. The table identifies implications for design or implementation

which arose during this project; and also highlights implications the researcher considers may

have a broader impact on the uptake of decision support tools within the health care sector

more generally.

Table 8-1: The implications of project themes

Theme Hospital scenario Community scenarioMissing information The value of an information element can be

determined by whether a health professional needs to pursue that information element for their decision-making – this suggests the inclusion of that information element into a model of essential information.

The implementation of an information model should suggest but not mandate the entry of essential information elements.

Information granularity and the language of health professionals

Information-based models and support tools for health professionals should reflect the information granularity evident in everyday practice and the ‘language’ used by health professionals. This poses a significant dilemma for the notion using categorisation for the exchange of information between systems and for the use of information for research.

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Conversation and communication

Conversation is a significant and very efficient way for health professionals to access contextual information and knowledge not available through other means.

Conversation also serves social and other roles and is highly valued by pharmacists. The information available through conversation is unlikely to be captured and structured for use within decision support systems and some roles cannot be duplicated within decision support systems.

Time constraints and summary information

Time was perceived to be a major influence in the ability to use decision support tools.

Time was a major influence for GPs to initiate referrals and cope with HMR reports received from pharmacists.

A concise, contextually-relevant summary of medication-related information is an approach to providing information for time-poor health professionals.

Decision support tools

The perception of what decision support tools are is influenced by the personal experiences of health professionals. It is difficult for health professionals to express requirements for decision support tools and to not be influenced by these experiences.

Alerts & reminders Alerts and reminders are perceived to be the most useful features of decision support tools. However, the acceptance of these features will be impacted upon severely by their usefulness (based on patient context), ability to access the appropriate information, repetition and impact on the work process.

The role for alerts and reminders in the context of a community-based decision support tool is still unclear but likely to be of limited application.

Systems for experts rather than expert systems

Pharmacists exhibit expert behaviours across the medication management continuum. Supporting the work practice of these individuals is better achieved by providing essential information to complement their professional knowledge, rather than attempt the onerous task of collecting and shaping the range of necessary information to support a range of patient and user contexts.

A technology-poor practice paradigm

The paucity of technology use in the community suggests the best technology will be the ‘right’ technology, implemented incrementally; and which is flexible and complements work flow. A document-oriented user interaction approach may be suitable.

The ‘viewpoints’ of professional practice tools

The viewpoints of GP desktop systems (and dispensing systems) do not support information sharing and preclude interfacing to concepts such as the digital document. GP desktop systems also ‘shape’ the information use of pharmacists.

Pharmacists’ perceptions of GPs in the HMR process

Many GPs are not convinced of the value of HMRs. Better communication between pharmacists and GPs, by a means such as the digital document, may improve communication and help with the uptake of; and value of HMRs to GPs.

The Practice nurse There may be a role for Practice Nurses to generate HMRs using the digital document to alleviate the problem of the number and quality of HMRs from GPs.

Complementary medicines (CMs) & Over-the-counter (OTC) medication

Information about CMs and OTCS is not routinely sought.

Information about CMs and OTCs is not routinely recorded in GP desktop systems. Pharmacists report the use of CMs and OTCs ‘alongside’ prescription medications/

Against the increasing use of CMs and OTCs in the community and potential for drug interactions with prescribed medications, there is a need capture use of these agents alongside prescription medications. There is an opportunity to do so with a shared record of medication-related information such as the digital document.

Table 8-1: The implications of project themes

Theme Hospital scenario Community scenario

Page 296

The evolution of the information model through the three iterations of the project is now

discussed in Section 8.4.

8.4 The evolution of the information modelThe information model and, consequently, its expression as a digital document underwent

three changes as a result of the iterations through the three research scenarios. Within each

scenario, analysis of the data suggested which information elements should be included in the

model and which additional functional requirements were needed in the digital document

prototype. A summary of these changes is shown in Figure 8-2. The figure shows the

transition of information elements in the model, represented as a series of documents.

Page 297

Figure 8-2: The evolution of the information model

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Page 298

Attention now turns to answering the questions which guided the project. The research in this

project was encapsulated in one main research question and a number of sub-questions.

These are brought together next in section 8.5.

8.5 research questionsThe main research question for this project was:


This complex was answered through a number of sub-questions used in the different phases

of the project, summarised in Figure 8-3. Each sub-question will be addressed on the way to

answering the main research question.

At the beginning of the project, prior to the investigation, two preliminary questions were

addressed by means of investigation of the relevant literature.


The researcher found there was very little evidence of suitable technology to support the

pharmacy profession with its medication-related decision-making other than for a few

Figure 8-3 Research questions in relation to research phases

Part 1 – The Hospital Scenario

Part 2 – The Community Scenario2A – Investigation of the



Literature review

Can we advance medication management for health consumers by supporting decision-making with a patient-

focused information model and technology-based intervention?

D. Can our intervention improve safety, quality and efficiency?E. What is the contribution of the information model?F. What is the contribution of the technology artefact (digital document)?


B. What is the best way of implementing this technology

approach?




Page 299

examples of relatively simple support tools and the traditional practice tools for dispensing and

information retrieval. This finding suggested a clear need to develop an appropriate tool to

support pharmacists with decision-making or additional information needs to support their

expanding, patient-centred medication management roles. The need for this project was

consequently justified.


The concept of a document metaphor, implemented as a digital document, was identified as a

suitable approach, promising to support information sharing and communication by means of

a metaphor familiar to health professionals. A document approach was also a good way to

satisfy the requirements for flexible information representation required for the dynamic and

complex health environment. Documents, by their nature, also offered other potential

advantages, such as support for some of the social aspects of the work.

As the need for the research was justified; and a technology approach for the project identified,

more specific research sub-questions could be addressed. These follow below.


The strategy for answering this first question was to understand information use by

pharmacists and medical officers involved in medication management within hospitals. The

hospital scenario was investigated first, as the researcher considered it to be a more

'information rich' environment, which would allow a fuller investigation of the issues

surrounding information use by health professionals. The medication management related

issues which emerged in this environment included:

• the inefficiency and uncertainty of decision-making due to the need to use disparate and

quite distinct sources of information

• the fact that information, particularly that related to medication, was often missing, which

led to concerns by medical officers and pharmacists about the effect on safety and

quality of life for patients

• the fact that conversation was an important method for pharmacists to seek missing

information – conversation was also a very important and efficient way of pharmacists

obtaining highly contextual patient-related information from other health professionals,

even when other sources of information were available

Page 300

• the prominent use of individual knowledge in medication-related decision-making of

pharmacists; and

• the differences between the information which health professionals: stated they would

like use; stated they did use; and were actually observed to use by the researcher.

The many difficulties experienced by pharmacists and doctors in accessing need information

suggested that technology could help address these issues through a shareable model of

essential information elements. This information model would need to cope with missing

information elements, recognise the use of personal knowledge; and represent and

communicate information in the same way that health professionals used information.


This question was addressed by investigating the potential for XForms technology to

implement the digital document which was based on the information model.

The researcher selected XForms as the underlying implementation technology based on

XForms' technical advantages such as: ease of authoring, flexibility; and the ability it provided

for the researcher to investigate alerts and reminders – while using a document-oriented view.

Despite some issues due to XForms being an evolving standard, the digital document

prototype was implemented as intended and the researcher's experience confirmed the

potential of XForms to realise a portable and dynamic document, suitable for supporting

information sharing and communication by health professionals.


This question was answered through benchtop testing of the digital document prototype by

accredited pharmacists. The major changes to the model were related to the inclusion of

patient information elements required in the community environment (e.g. reasons for referral),

or supporting physical information (e.g. falls etc.) which were not available to the community

pharmacists (compared with their hospital colleagues). The inclusion of these information

elements actually reflected the similar information needs of community and hospital

pharmacists. But, in the case of community pharmacists, the model required extensions to

make up for the unavailability of information sources (including conversation) available to their

hospital colleagues – although the depth of information required by community pharmacists

Page 301

was less, as patient management is concerned with (more stable) chronic disease compared

to the acute disease episodes experienced in hospitals. The main intention of community

pharmacists was supporting patients in managing at home and, consequently, in keeping

patients out of hospital. Further, in the community, the document needed to be 'context-aware'

of its use, depending on whether it was used by the GP for referral, or by the pharmacist for

the HMR.


This question was answered by field study interventions into the HMR setting in the

community. This intervention, though limited in terms of the number of subjects, was sufficient

for GPs and pharmacists to perceive benefits for the medication management process, health

professionals; and patients. There were a number of contributions to safety:

• encouraging the collection of information relevant to medication management-related

decision-making, thus increasing the chances of errors being detected and corrected by

pharmacists

• increased accuracy of medication-related information as the result of document sharing

by health professionals

• more timely sharing and better availability of information for the GP, so that patient

recommendations from pharmacists could be effected more quickly by GPs

• encouraging pharmacists to move from hand-written reports

Although these safety gains were perceived, they would need to be confirmed through more

extensive field studies.

Quality was examined under system and information headings, but the researcher believes

information quality was the most important issue for pharmacists carrying out home medication

reviews, both from the perspective of the review process and that of the report. Quality

improvements were perceived by the:

• use of standardised essential information elements to guide pharmacists with the depth

and quality of information required for HMR reporting – this was also seen to assist

pharmacists with quality assurance evaluations

• move away from hand-written reports

• ability to communicate a succinct summary of essential information to the GP in a timely

manner; and

• potential for pharmacists to receive GP feedback though an action plan

Efficiency was illustrated in two ways, through improvements in:

Page 302

• the timeliness of information; and

• availability of information.

This would allow patient-related decisions to be made more quickly by the GP and facilitate

feedback to the pharmacist.


The model provides a template of essential medication-related information which is succinct,

relevant and can be understood and shared by health professionals. This was reinforced by

the model’s ability to be used in different medication management scenarios. Thus, the

principal contribution of the information model is a relevant framework for medication

management-related information.


The digital document allows a flexible way of communicating and sharing medication-related

information through a simple, easy-to-use artefact. The document-centric approach is a

comfortable fit with health professionals’ practice. The ability to provide some dynamic

functionality has limited, although potentially useful application. In brief, the principle

contribution of the digital document is its natural fit with the work environment and its flexibility

in use and communication.

The researcher now returns to the main question for this research project.


The answer to this question is 'yes'. However, this answer is contingent on the approach used

to develop the technology used in the intervention. This project has identified a number of

important, information-related issues which can affect decision-making in the practice area of

medication management, including: missing information, the context of information use; and

the relationship of information use by health professionals alongside use of their personal

knowledge. These factors all affect the approach to designing and implementing technology

tools. An affirmative answer, based on this project, is therefore contingent on the use of the

correct technology, as a complement to, rather than an intruder into, human decision-making.

Page 303

The suggested contributions of this research to theory and practice are now discussed in

Section 8.6.

8.6 Research contributions

8. 6.1 Contributions to theoryThis project has contributed to the development of theory in the area of medical information

models, especially those relating to the support of medication management, as well as to the

understanding of the support role offered by a digital document as the potential means of

implementation of such a model.

• Decision support theory has tended to concentrate on: the identification and

development of taxonomies or guidelines suitable for inclusion into a DSS software

implementation; knowledge translation into active rules; and development of software

which appropriately combines the knowledge and rules (and local data) to provide

appropriate decision support functionality on a user’s desktop. This research project, by

contrast, has focused on identifying the issues which underpin the development of the

information model. A particularly important finding is that decision-making can be most

effectively supported by a collection of essential information elements as a complement

to human knowledge, rather than attempting to represent all information and knowledge

within a model. This stance acknowledges the difficulty of categorising complex, health-

related information; the need for humans to apply information in a wide variety of

differing and variable contexts; and the manner in which health care professionals use

and communicate language which is meaningful for their purposes. These findings cast

a different light on the analysis of both decision support and expert systems – and make

a significant contribution to theory in the area of medical support systems.

• The role of the document, in either paper or electronic form, to represent and

communicate information is well understood. The role of paper-based documents in

Health is also well known. This project has added to this knowledge by confirming the fit

of a digital document for the process of the medication management for doctors and

pharmacists; and that the digital document can serve as a suitable boundary object

between these practice groups in Health. An important finding was that the application of

dynamic properties of digital documents may be limited, as these documents exist in an

environment of information uncertainty. These results suggest both that there is great

promise for the use of digital documents in Health; but that at the same time the

complexity of the health care environment demands particular attention.

Page 304

• Finally, the project adds to the empirical evidence for the need for decision support tools

for pharmacists involved in medication management, particularly the emerging

community role of medication reviews. It does this while identifying issues which affect

the approach to development and implementation, or the success of these tools.

8. 6.2 Contributions to practiceThis project has contributed to medication management practice by suggesting a framework

which can be used to improve the conduct of medication reviews. Further, the project has

identified problems and possible solutions which can contribute to the better uptake of

technology in the area of medication management and, in general.

• The digital document approach in this project provides a framework which can be used

to improve the sharing and communication of relevant medication-related information

between doctors and pharmacists. This promises gains in safety, quality and efficiency

of the medication management process; and ultimately improvements in outcomes for

patients.

• The project has identified that sophisticated technology is not required to implement

changes in the medication management environment. The approach is one of providing

the ‘right’ technology which accommodates the work processes of individuals – a

‘lightweight’ approach advocated the project, using the digital document, is adequate for

supporting a paradigm change in the community.

• The project has diagnosed issues that impact on the conduct of medication reviews in

the community. The inability of existing medical and pharmacy systems to represent

actual current medication taken by patients suggests that practice of medication

management may not be served adequately by a single decision support tool.

• Opportunities for practice improvement have also been suggested: an approach to

enable the recording of complementary and over-the-counter medications, addressing a

current practice problem; and an opportunity to improve the number and quality of home

medication review referrals through the involvement of other health professionals (the

medical practice nurse).

• Future work suggested by the project (and one project already begun) suggests other

opportunities to contribute to improved patient outcomes in the area of medication

management and, more broadly in Health.

This chapter now concludes with suggestions for future work in Section 8.7.

Page 305

8.7 Future workThe future work suggested here is based on opportunities envisaged during the project; and is

expressed as high level concepts. Clearly, issues such as technology infrastructure and

privacy/security would need to be considered more fully in these future projects than they have

in the present project. In addition, redevelopment of the proof of concept digital document

might well require redevelopment in other languages or on other platforms.

8. 7.1 More extensive field trialsThe project began with the understanding that results would be indicative and that, as a proof

of concept, wider extrapolation of results would be inappropriate. Participants in field studies

did perceive benefits, particularly with communication and how information could be better

shared. They also considered there would be benefits to medication management for safety,

quality and efficiency. But as the researcher was not able to directly measure benefits, more

extensive field trials are now required. As GPs and pharmacists fall into informal geographical

groups around patients requiring HMRs, opportunities for trials within these community

'networks' would be both possible and appropriate.

8. 7.2 A ‘working document’ for medication management in a hospitalThis suggestion arose during testing of the digital document by the Hospital Outreach

Medication Review pharmacists. These pharmacists used a paper medication and allergy

history tracking form within the hospital and a further medication transfer summary form to

convey patients’ medication information to GPs. The close fit of the digital document to the

purposes of both these forms suggested the digital document’s use as a shared ‘working

document’ to achieve both functions, with interest shown by this group as a possible future

project. This project has already begun within the University of South Australia.

8. 7.3 HMR referral generation by Practice Nurses The Practice Nurse played a significant role in medical practices, this role emerging as a

‘theme’ in the project. As discussed earlier, Practice Nurses are ideally placed in the

communication pathway to GPs, have access to patient data and are already involved in

patient-related activities such as performing health assessments. In light of the time constraint

on GPs which causes problems in the number and quality of HMRs being generated, there

may be a role for Practice Nurses to generate HMRs using the digital document.

8. 7.4 A digital document approach in an Aged Care FacilityThe intent of a review in an Aged Care Facility (ACF) is the same as that of an HMR and the

digital document in its present state would come close to supporting this. The digital document

was tested only on a few ACR reviews but did not identify any issues that would obviate or

even limit its use for such a purpose. In the ACF scenario, in the absence of any other systems,

the digital document could become a current medication record, useful to facility staff, the

Page 306

reviewing pharmacist and the visiting GP. With the possibility of on-line sharing, remote access

by the GP would also be possible.

8. 7.5 A digital document approach for information exchange for discharged hospital cardiac patientsInterest was expressed by an adult hospital to use the digital document for cardiac patients

discharged into the community. As a high-risk group, these cardiac patients required an HMR

to be undertaken within a short period once in the community to ensure that they were

managing their medication appropriately. Part of this hospital’s needs was to communicate the

relevant information to the HMR pharmacists; and then the HMR pharmacists’ review

information back to hospital. The leader of the hospital project (who was also head of the

cardiac unit) suggested signalled his interest in discussing the results of the project with the

researcher.

8. 7.6 A portable medication recordThe portability of the digital document suggested its use as a mobile medication record for

patients. This was suggested by a GP who saw an opportunity for using the digital document

on a USB drive, so the patient could take their medication records with them to the GP, or for

emergency visits etc. This could be achieved using a similar approach to the local use of the

document, e.g. using a Visual Basic form and browser (such as Firefox Portable®) stored on

a USB drive. There would be issues to consider such as loss and size of the device, privacy

and security etc. However, this approach may be promising as USB drives are more likely to

be able to connect easily to relatively recent computers (compared to e.g. Smartcards that

would require dedicated device readers and software). The advantages here would be that the

GP, community pharmacist and hospital pharmacist could all contribute to maintaining the

currency of the information on the USB record when they were with the patient.

8. 7.7 A digital document approach for patient groups with extensive medica-tion use As well as the elderly patient population targeted in this project, there are other groups of

individuals that have extensive medication use because of chronic illness. From the

researcher’s experience in a Women’s and Children’s hospital, two pertinent groups are

patients with Cystic Fibrosis and Oncology patients. Both of these groups can be diagnosed at

a very early age, have treatment and support that heavily involves the use of medication and

nutrition and are users of complementary medicines. There is a great deal of effort required of

these patients and their parents or guardians to manage medications. The digital document

approach, either on-line or as local record may help by providing a shareable, maintainable

current record. The approach of a portable record perhaps may be particularly useful in an

adolescent context. There is also a more general question of how useful the approach of a

portable record might be in a general paediatric context, for use by parents.

Page 307

8. 7.8 A shared record with health consumersIt is ironic that the term ‘patient-focused’ usually fails to include the direct involvement of the

patient. As suggested during the field study, there may be an opportunity for the digital

document, or at least the information contained in it, to be shared amongst a number of users

(the patient, the pharmacist and the GP). However, in light of the evidence suggesting that

involving patients more directly in decision-making about their own health can lead to better

medication adherence and better outcomes, the logical step would be to involve consumers

directly. The potential is there with the digital document approach – it would be a very

interesting project looking at which consumers wanted to share their medication information

with health professionals; and also the attitude of health professionals who would no longer

‘control’ the record.

8. 7.9 A shared record with other health professionalsAs the idea of much future work is about sharing information, other useful projects may involve

medication-related information-sharing by health professionals other than GPs and

pharmacists e.g. district nurses and community pharmacists. The (district) nursing profession

increasingly provides care to patients in the home that includes the administration of

medications. A current medication record may be of use to this group, although it is difficult to

suggest what value this would be without greater knowledge of what current district nursing

processes entail.

8. 7.10 GP information behaviour with GP desktop systemsThis project brought to light the reliance of pharmacists on the information contained in the GP

desktop systems. A study of GP data entry habits with their GP desktop systems may shed

some light what issues affect the amount and quality of information that GPs enter into these

systems. This could provide suggestions to improve the information contained in those

systems to the mutual benefit for the GP and the pharmacist dependant on that information for

medication reviews.

Page 308

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Appendices

As described at the beginning of this thesis, all appendices are contained on CD-ROM as PDF-formatted files. The file names are prefixed by the Appendix number as shown in the list below:

Appendix AA-Field Studies XForms Code.pdf

Appendix A-Analysis of Pharmacy DS Literature.pdf

Appendix AB-Field Studies Patient XML File.pdf

Appendix AC-Field Studies XSL Code.pdf

Appendix AD-Bibliography.pdf

Appendix B-An investigation of Methodology.pdf

Appendix C-HMR Quality Assurance Form.pdf

Appendix D-HOT Fit Model items.pdf

Appendix E-Hospital Ethics Approval & Correspondence.pdf

Appendix F-Benchtop Testing Ethics Approval.pdf

Appendix G-Field Studies Ethics Approval.pdf

Appendix H-Pharmacist Questionnaire.pdf

Appendix I-Medical Officer Questionnaire.pdf

Appendix J-Hospital Full Analysis.pdf

Appendix K-Hospital Technical & Development.pdf

Appendix L-Hospital VB Viewer Code.pdf

Appendix M-Hospital XForms Code.pdf

Appendix N-Hospital Patient XML File.pdf

Appendix O-Benchtop Full Analysis.pdf

Appendix P-Benchtop Technical & Development.pdf

Appendix Q-Development Record (Excel).pdf

Appendix R-Benchtop VB Viewer Code.pdf

Appendix S-Benchtop ASP Code.pdf

Appendix T-Benchtop XForms Code.pdf

Appendix U-Benchtop Patient XML File.pdf

Appendix V-Benchtop XSL Code.pdf

Appendix W-Benchtop Comparison of Model Elements.pdf

Appendix X-Field Studies Full Analysis.pdf

Appendix Y-Field Studies Additional Forms.pdf

Appendix Z-Field Studies Technical & Development.pdf

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