SELF-­‐MANAGEMENT  &  INFORMATICS     1  

This is the pre-peer reviewed version of the following article: Knight, E. P. and Shea, K. (2014), A Patient-Focused Framework Integrating Self-Management and Informatics. Journal of Nursing Scholarship, 46: 91–97. doi: 10.1111/jnu.12059, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/jnu.12059/abstract

A Patient-Focused Framework Integrating Self-Management and Informatics

Elizabeth P. Knight, BSN, RN (corresponding author) Beta Mu Chapter, STTI

PhD/DNP Student University of Arizona College of Nursing

Tucson, Arizona eknight@email.arizona.edu

Kimberly Shea, PhD, RN Beta Mu Chapter, STTI

Assistant Professor University of Arizona College of Nursing

Tucson, AZ kshea@email.arizona.edu

SELF-­‐MANAGEMENT  &  INFORMATICS           2  

Abstract

Purpose: This paper introduces a framework to 1) guide chronic illness self-management interventions through the integration of self-management and nursing informatics, 2) focus self-management research, and 3) promote ethical, patient-empowering technology use by practicing nurses. Method: Existing theory and research focusing on chronic illness, self-management, health-enabling technology, and nursing informatics was reviewed and examined and key concepts were identified. A care paradigm focusing on concordance, rather than compliance, served as the overall guiding principle. Findings: This framework identifies key relationships among self-management (patient behaviors), health force (patient characteristics) and patient-defined goals. The role of health-enabling technology supporting these relationships is explored in the context of nursing informatics. Conclusions: The Empowerment Informatics framework can guide intervention design and evaluation and support practicing nurses’ ethical use of technology as part of self-management support. Clinical Relevance: Nurses worldwide provide support to patients who are living with chronic illnesses. As pressures related to cost and access to care increase, technology-enabled self-management interventions will become increasingly common. This patient-focused framework can guide nursing practice using technology that prioritizes patient needs.

Key words: Chronic illness, chronic disease, self-management, informatics, technology, framework, theory, patient-focused

SELF-­‐MANAGEMENT  &  INFORMATICS           3  

A Patient-Focused Framework Integrating Self-Management & Informatics

Chronic illness is a leading cause of death and disability globally (World Health

Organization, 2011). Nearly one in two U.S. adults lives with a chronic illness, such as

diabetes, heart disease, or arthritis, and prevalence is rising (National Center for Chronic

Disease Prevention and Health Promotion, 2009). Unlike acute illnesses which can be

managed in a healthcare setting, chronic illness is managed largely by individuals and

families at home as part of their daily lives. Although the U.S. healthcare system

prioritizes acute care, rising costs and patient preferences for aging in place are driving

demand for different approaches to care, including self-management support (Wiles,

Leibing, Guberman, Reeve, & Allen, 2012).

Technology-enabled self-management interventions are ubiquitous; however,

there is limited evidence of lasting improvements in patient outcomes or cost savings.

The root of this problem may be a lack of theoretical guidance: interventions are 1)

convenience-based use of available technologies in existing disease-management plans,

and/or 2) compliance-based, designed to help patients meet the goals defined by

healthcare providers within a structured, acute-care based health system.

While existing nursing theory examines how patients self-manage, and existing

informatics theory explores nurses’ technology use, there is currently no framework

addressing the intersection of these ideas. This paper will introduce a framework to guide

the integration of self-management and informatics research and to promote ethical,

patient-empowering technology use by practicing nurses.

Understanding Self-Management

Self-management typically refers to a core set of behaviors undertaken by patients

SELF-­‐MANAGEMENT  &  INFORMATICS           4  

living with chronic illness: medical management, role management, and emotional

management (Corbin & Strauss, 1988; Lorig & Holman, 2003). A considerable body of

theory and research explores patients’ experiences of self-management (Corbin &

Strauss, 1988; Grey, Knafl, & McCorkle, 2006; Lorig & Holman, 2003; Ryan & Sawin,

2009; Schulman-Green et al., 2012). The nurse’s approach to supporting patients’ self-

management behaviors, informed by this work, is the basis of a patient-focused self-

management intervention.

Self-Management Interventions and Technology

Many existing technology-based interventions rely on a compliance-based

approach to self-management that aims to increase patient adherence to provider-defined

plans and goals. Such interventions focus on medical management, but often ignore the

other aspects of self-management. Telemonitoring devices that collect and send

physiologic data to a home health nurse are an example of technology designed to

improve compliance with prescribed medical regimens (LaFramboise, Woster, Yager, &

Yates, 2009; Woodend et al., 2008; Woods & Snow, 2013). Electronic and web-based

tools that enable the patient to track patterns in their vital signs and adjust management

according to an algorithm are also compliance-based (Brennan et al., 2010; Seto et al.,

2012).

Concordance and Self-Management

Alternatively, in a concordance-based approach, the patient learns how to live

with a chronic health condition and is empowered and motivated by relevant knowledge,

practical skill, and personal experience (Schermer, 2009). A concordance approach can

better address all core behaviors of self-management, including medical, role, and

SELF-­‐MANAGEMENT  &  INFORMATICS           5  

emotional management. While each health-related action may not be the most medically

appropriate from the provider’s perspective, the patient makes choices in accordance with

his personal goals and values (Schermer, 2009). The concordance approach requires

collaboration between nurse and patient and is the focus of the framework described in

this paper. The collaborative nurse offers information and guidance, but also recognizes

that consideration of the patient’s unique characteristics, rather than standardized clinical

targets, are the ultimate priority in self-management.

Unique Patient Characteristics

Supporting individual patient goals requires an understanding of the contexts in

which patients live with and manage their chronic illnesses, both internally (cognition

and emotion) and externally (environment and resources) (Forbes & While, 2009).

Health Force

Health force is the strength of the patient’s belief that he can actualize his own

unique concept of health. It is influenced by sociocultural and contextual factors

combined with aspects of individual experience, knowledge, values, and motivation.

Health force is personal and dynamic and may shift with the patient’s education, access

to resources, health status, and life experiences. Thus, health force is a patient

characteristic which contributes to the patient’s desire and ability to engage in self-

management behaviors.

Others have suggested that self-management is mediated by self-efficacy (Lorig

et al., 2010). Determinants of self-efficacy defined by Bandura, including social

persuasion, vicarious experience, and personal mastery, may also influence health force

(Bandura, 1998). However, the concept of health force extends the situation-specific

SELF-­‐MANAGEMENT  &  INFORMATICS           6  

nature of self-efficacy beyond individual tasks to the patient’s personal concept of health.

Understanding health force will help the nurse identify patient-focused mediators and

moderators of successful self-management, and ultimately empower the patient to pursue

self-defined goals.

Patient-Defined Goals

Self-management (patient behaviors) and health force (patient characteristics)

together contribute to the achievement of meaningful goals. Individually meaningful

goals promote patient autonomy, empowerment, and motivation (Holm, 2005). These

goals are not terminal outcomes, but rather part of the ongoing, dynamic process of self-

management (McWilliam et al., 1999). Goals may shift over time with patients’ health

status, knowledge, and circumstances. They may be objective and measureable or

subjective and personal. By supporting patient empowerment through individualized

goal-setting, nurses can help patients focus on health as they themselves experience it,

rather than on illness as measured by healthcare providers.

Individuals may choose to use empirical measurements of health directly in their

goals, or nurses may use objective data to assist patients in achieving their subjective

goals. For instance, nurses may help patients identify patterns and relationships among

their goals, such as symptom control, measurable indicators, such as vital signs, and

behaviors, such as exercise. Empirical measurements can also assist with medical

management, which is one of the behaviors of self-management. Ultimately, however,

empirical health indicators are useful primarily as a support for patient-defined goals.

Health-Enabling Technologies

Health-enabling technologies (HET) are information and communication

SELF-­‐MANAGEMENT  &  INFORMATICS           7  

technologies which create conditions for sustainable, patient-empowering health choices

(Haux et al., 2009). Patients’ direct interaction with HET increases their access to and

control over information, removes barriers to empowerment, and assists them to sustain

their self-management behaviors after professional intervention has ended. HET-enabled

self-management has the potential to address high healthcare burdens worldwide by

enhancing chronic disease management, regardless of accessibility to local healthcare

resources (Dacso, Knightly, & Dacso, 2011).

Strengths of current HET include personalizability, portability, adaptability, data

collection and management, and multimodal communication (Arsand & Demiris, 2008;

Forbes & While, 2009). HET functions useful for self-management include monitoring,

education, feedback, social support, and procedural response.

HET is deliberately defined broadly to allow ongoing integration of new

innovations. However, interventions driven by available technology rather than by

identified needs of users and theoretical guidance often fail to produce meaningful

outcomes (Vicente, 2003). Thus, a framework guiding the use of HET needs theoretical

structure to facilitate the appropriate and efficient integration, implementation, and

evaluation of new technologies. The field of nursing informatics is one potential source

of this needed theoretical structure.

Nursing Informatics

Nursing informatics is defined as the integration of data, information, and

knowledge to support patients and nurses in decision making across roles and settings,

using information structures, processes, and technology (Staggers & Thompson, 2002).

Nursing informatics frameworks have been used primarily in reference to nurses in

SELF-­‐MANAGEMENT  &  INFORMATICS           8  

hospital settings, but some may also be useful to guide community-based self-

management. The Informatics Research Organizing Model (Effken, 2003) can guide the

development of community-based HET interventions within a nursing worldview. The

explicit inclusion of the four concepts of the nursing metaparadigm (person, environment,

health, and nursing) promotes interventions that are context-aware and patient-focused

(Fawcett, 1996), characteristics necessary to support a concordance approach. The Data,

Information, Knowledge and Wisdom informatics framework provides a nursing process

approach to understanding technology’s role in self-management (Gee et al., 2012).

While previously this framework has been applied to nurses’ technology use, it may also

guide the collaboration of patient and nurse using HET by focusing on the role of

patients’ unique self-knowledge in self-management (Gee et al., 2012).

Human-Computer Interaction

Effective technology use requires not only knowledge of hardware and software

capabilities, but also an understanding how people cognitively and physically interact

with interfaces. Potential sources of theory to explicate these relationships include the

field of human factors, which explores how technology is both useful and usable (Czaja

& Lee, 2002; Demiris et al., 2010; Vicente, 2003), and sociotechnical theory, which

explores the influence of complex contextual factors on information technology tools

(Fox, 1995; Westbrook et al., 2007). A framework integrating theory that examines the

intersection of man and machine will promote theory-driven interventions rather than

one-sided, technology-driven interventions.

The Empowerment Informatics Framework

The empowerment informatics (EI) framework (Figure 1) suggests that patients

SELF-­‐MANAGEMENT  &  INFORMATICS           9  

living with chronic illnesses and collaborating nurses can use HET to support the

relationships among patients’ behaviors (self-management), patients’ unique

characteristics and context (health force), and patients’ individual goals. Self-

management plans informed by patient values, needs, and strengths can promote shared

understanding and mutual goals as part of a concordance, rather than compliance,

approach (Gunson & Chawngthu, 2012). The patient is empowered and motivated

through this focus on his own concept of health rather than on externally specified targets

enforced by healthcare providers. Patients’ behaviors directed at individual goals still

affect empirical indicators of their health and their use of resources; however, these

effects are secondary.

Existing theories related to self-management, technology, nursing, and

informatics can be integrated and tested within the EI framework. This theoretical

grounding, combined with a focus on patients’ individual goals, can begin to address the

weaknesses in current self-management interventions and drive truly innovative

approaches to managing chronic illness in the community.

Implications for Research

The EI framework aids in the identification of the goals of self-management

interventions, and consequently, the outcomes of interest. The outcomes of interest for EI

interventions are twofold: both the patient’s subjective perception of his health and

objective individual and systems-level effects are essential parts of evaluation. Most

studies to date have looked at only one of these aspects and have thus failed to capture

and communicate the overall potential impact of the interventions.

Evaluating Patient Perspectives

SELF-­‐MANAGEMENT  &  INFORMATICS           10  

The patient’s perspective on his own health is reflected in individual goals that

may shift over time in response to changes in health, environment, knowledge, and other

factors. Qualitative evaluation is most conceptually appropriate to evaluating these

subjective individual perspectives (Rahimpour, Lovell, Celler, & McCormick, 2008;

Sanders et al., 2012). Alternatively, researchers may use self-report tools to measure

constructs related to individual perception of health. Although the nurse cannot truly

measure the patient’s individual experience in a standardized fashion, in practice,

measurable constructs such as quality of life, self-perception of health, or satisfaction

with care may be useful in describing overall trends and common experiences among

groups of patients (Brennan et al., 2010; Lorig et al., 2012).

Evaluating Empirical Outcomes

The EI framework also supports quantitative research. While it is essential to

demonstrate that an intervention is subjectively valuable to patients, healthcare systems

that focus on evidence-based practice and cost control demand evidence of the

intervention’s objective clinical and economic benefit. Empirical, quantitative data can

communicate both individual-level and systems-level results in terms that will be widely

understood and will facilitate adoption. Objective evaluation in self-management

intervention studies may include process outcomes, functional outcomes, or clinical and

systems-level outcomes (Stellefson et al., 2013). Process outcomes include self-efficacy,

perceived usefulness, and frequency of communication with healthcare providers.

Functional outcomes quantify behaviors such as physical activity and medication

adherence. Clinical and systems-level outcomes include symptoms, physiologic data,

SELF-­‐MANAGEMENT  &  INFORMATICS           11  

laboratory values, mortality and hospital readmissions (Lorig et al., 2012; Woodend et

al., 2008;. Radhakrishnan & Jacelon, 2012; Stellefson et al., 2013).

Future Research

Research is needed to test the relationships between the concepts in this

framework, thereby leading to a better understanding of the unique contributions of HET

to the processes of self-management. Previously hypothesized determinants of successful

self-management (e.g., self-efficacy, self-confidence) need to be reevaluated in the

context of the EI framework. Understanding the mechanisms by which an intervention

works offers valuable direction for further research (Pingree et al., 2010). Research is

needed identify or confirm key mediators and moderators of the relationships proposed in

this framework.

Implications for Nursing Practice

Nurses working in diverse settings worldwide provide support to patients who are

living with chronic illnesses. HET self-management interventions are widely used, but

many are driven by economic and technological factors rather than patient factors

(Kaplan & Litewka, 2008). Consequently, the degree to which they meet patients’ needs,

in addition to healthcare providers’ or organizations’ needs, varies widely. Concerns

surrounding the use of HET by nurses include privacy, intrusiveness, autonomy, and

patient-centeredness (Demiris, Doorenbos, & Towle, 2009; Kaplan & Litewka, 2008).

The EI framework addresses many of these issues; it is driven by and focused on patient

goals, characteristics, and contexts and can help guide nurses in an ethical, patient-

focused approach to these issues.

SELF-­‐MANAGEMENT  &  INFORMATICS           12  

Nurses may be unaware of the paradigm underlying their care and despite

professing to promote patient empowerment, they may continue to practice in a way that

perpetuates medical dominance (Wilkinson & Whitehead, 2009). The use of this

explicitly patient-focused framework ensures emphasis on concordance, which empowers

patients, rather than compliance, which perpetuates medical dominance. Nursing values

espoused in the EI framework include focusing on quality of life, freedom of choice,

dignity, and personal health patterns based on values (Gunson & Chawngthu, 2012).

Conclusions

The growing worldwide burden of chronic illness and the imperative to reduce

healthcare costs will continue to create demand for technology-based self-management

interventions. The EI framework introduced in this paper suggests a patient-focused

approach to the integration of theory and evidence surrounding self-management and

nursing informatics. Research is needed to test these proposed relationships. This

introduction will serve to guide the use of the EI framework in nursing research and

practice.

SELF-­‐MANAGEMENT  &  INFORMATICS           13  

Clinical Resources Internet self-management programs: http://patienteducation.stanford.edu/internet/ Nursing informatics resources: http://www.amia.org/programs/working-groups/nursing-informatics Nursing theory: http://currentnursing.com/nursing_theory/

References

Arsand, E., & Demiris, G. (2008). User-centered methods for designing patient-centric self-help tools. Informatics for Health & Social Care, 33(3), 158–169. doi:10.1080/17538150802457562

Bandura, A. (1998). Health promotion from the perspective of social cognitive theory. Psychology & Health, 13(4), 623–649. doi:10.1080/08870449808407422

Bowles, K. H., Riegel, B., Weiner, M. G., Glick, H., & Naylor, M. D. (2010). The effect of telehomecare on heart failure self care. AMIA Annual Symposium Proceedings / AMIA Symposium, 2010, 71–75.

Brennan, P. F., Casper, G. R., Burke, L. J., Johnson, K. A., Brown, R., Valdez, R. S., et al. (2010). Technology-enhanced practice for patients with chronic cardiac disease: Home implementation and evaluation. Heart & Lung : The Journal of Critical Care, 39(S), S34–S46. doi:10.1016/j.hrtlng.2010.09.003

Corbin, J. M., & Strauss, A. (1988). Unending work and care: Managing chronic illness at home. San Francisco, CA: Jossey-Bass.

Czaja, S. J., & Lee, C. C. (2002). Designing computer systems for older adults. In J. A. Jacko & A. Sears (Eds.), The Human-computer interaction handbook (pp. 413–427). Mahwah, NJ: L. Erlbaum Associates Inc.

Dacso, C. C., Knightly, E., & Dacso, M. (2011). Technology-enabled chronic disease management in under-resourced environments. Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief, 365–369.

Demiris, G., Charness, N., Krupinski, E., Ben-Arieh, D., Washington, K., Wu, J., & Farberow, B. (2010). The role of human factors in telehealth. Telemedicine and e-Health, 16(4), 446–453. doi:10.1089/tmj.2009.0114

Demiris, G., Doorenbos, A. Z., & Towle, C. (2009). Ethical considerations regarding the use of technology for older adults: The case of telehealth. Research in Gerontological Nursing, 2(2), 128–136. doi:10.3928/19404921-20090401-02

Effken, J. A. (2003). An organizing framework for nursing informatics research. CIN: Computers, Informatics, Nursing, 21(6), 316–25.

Fawcett, J. (1996). On the requirements for a metaparadigm: an invitation to dialogue. Nursing Science Quarterly, 9(3), 94–106.

Forbes, A., & While, A. (2009). The nursing contribution to chronic disease management: A discussion paper. International Journal of Nursing Studies, 46(1), 120–131. doi:10.1016/j.ijnurstu.2008.06.010

Fox, W. M. (1995). Sociotechnical system principles and guidelines: past and present. The Journal of Applied Behavioral Science, 31(1), 91–105.

Gee, P., Greenwood, D., Kim, K., Perez, S., Staggers, N., & DeVon, H. (2012). Exploration of the e-patient phenomenon in nursing informatics. Nursing Outlook, 60(4), e9–e16. doi:10.1016/j.outlook.2011.11.005

SELF-­‐MANAGEMENT  &  INFORMATICS           14  

Grey, M., Knafl, K., & McCorkle, R. (2006). A framework for the study of self- and family management of chronic conditions. Nursing Outlook, 54(5), 278–286. doi:10.1016/j.outlook.2006.06.004

Gunson, J., & Chawngthu, L. (2012). Health Economics and Informatics: The gap-fit of current healthcare and Parse practice. Nursing Science Quarterly, 25(2), 176–181. doi:10.1177/0894318412437948

Haux, R., Gietzelt, M., Hellrung, N., Ludwig, W., Marschollek, M., Song, B., & Wolf, K. (2009). Health-enabling technologies for pervasive health care: a pivotal field for future medical informatics research education? Studies in Health Technology and Informatics, 150, 14–16.

Holm, S. (2005). Justifying patient self-management--evidence based medicine or the primacy of the first person perspective. Medicine, Health Care, and Philosophy, 8(2), 159–164. doi:10.1007/s11019-005-2280-x

Kaplan, B., & Litewka, S. (2008). Ethical challenges of telemedicine and telehealth. Cambridge Quarterly of Healthcare Ethics, 17(4). doi:10.1017/S0963180108080535

LaFramboise, L. M., Woster, J., Yager, A., & Yates, B. C. (2009). A technological life buoy: Patient perceptions of the Health Buddy. The Journal of Cardiovascular Nursing, 24(3), 216–224.

Lorig, K. R., & Holman, H. R. (2003). Self-management education: history, definition, outcomes, and mechanism. Annals of Behavioral Medicine, 26(1), 1–7.

Lorig, K., Ritter, P. L., Laurent, D. D., Plant, K., Green, M., Jernigan, V. B. B., & Case, S. (2010). Online diabetes self-management program: A randomized study. Diabetes Care, 33(6), 1275–1281. doi:10.2337/dc09-2153

Lorig, K., Ritter, P. L., Plant, K., Laurent, D. D., Kelly, P., & Rowe, S. (2012). The South Australia health chronic disease self-management internet trial. Health Education & Behavior. doi:10.1177/1090198112436969

McWilliam, C. L., Stewart, M., Brown, J. B., McNair, S., Donner, A., Desai, K., et al. (1999). Home-based health promotion for chronically ill older persons: Results of a randomized controlled trial of a critical reflection approach. Health Promotion International, 14(1), 27–41.

National Center for Chronic Disease Prevention and Health Promotion. (2009). Chronic disease: The power to prevent, the call to control. Retrieved from: http://www.cdc.gov/chronicdisease/resources/publications/aag/pdf/chronic.pdf

Nguyen, H. Q., Donesky-Cuenco, D., Wolpin, S., Reinke, L. F., Benditt, J. O., Paul, S. M., & Carrieri-Kohlman, V. (2008). Randomized controlled trial of an internet-based versus face-to-face dyspnea self-management program for patients with chronic obstructive pulmonary disease: Pilot study. Journal of Medical Internet Research, 10(2). doi:{10.2196/jmir.990}

Pingree, S., Hawkins, R., Baker, T., duBenske, L., Roberts, L. J., & Gustafson, D. H. (2010). The value of theory for enhancing and understanding e-health interventions. American Journal of Preventive Medicine, 38(1), 103–109. doi:10.1016/j.amepre.2009.09.035

Radhakrishnan, K., & Jacelon, C. (2012). Impact of telehealth on patient self-management of heart failure: a review of literature. Journal of Cardiovascular Nursing, 27(1), 33–43. doi:10.1097/JCN.0b013e318216a6e9

Rahimpour, M., Lovell, N. H., Celler, B. G., & McCormick, J. (2008). Patients'

SELF-­‐MANAGEMENT  &  INFORMATICS           15  

perceptions of a home telecare system. International Journal of Medical Informatics, 77(7), 486–498. doi:10.1016/j.ijmedinf.2007.10.006

Ryan, P., & Sawin, K. J. (2009). The Individual and family self-management theory: Background and perspectives on context, process, and outcomes. Nursing Outlook, 57(4), 217–225.e6. doi:10.1016/j.outlook.2008.10.004

Sanders, C., Rogers, A., Bowen, R., Bower, P., Hirani, S., Cartwright, M., et al. (2012). Exploring barriers to participation and adoption of telehealth and telecare within the Whole System Demonstrator trial: A qualitative study. BMC Health Services Research, 12. doi:10.1186/1472-6963-12-220

Schermer, M. (2009). Telecare and self-management: opportunity to change the paradigm? Journal of Medical Ethics, 35(11), 688–691. doi:10.1136/jme.2009.030973

Schulman-Green, D., Jaser, S., Martin, F., Alonzo, A., Grey, M., McCorkle, R., et al. (2012). Processes of self-management in chronic illness. Journal of Nursing Scholarship, 44(2), 136–144. doi:10.1111/j.1547-5069.2012.01444.x

Seto, E., Leonard, K. J., Cafazzo, J. A., Barnsley, J., Masino, C., & Ross, H. J. (2012). Perceptions and experiences of heart failure patients and clinicians on the use of mobile phone-based telemonitoring. Journal of Medical Internet research, 14(1). doi:10.2196/jmir.1912

Staggers, N., & Thompson, C. B. (2002). The evolution of definitions for nursing informatics: a critical analysis and revised definition. AMIA, 9(3), 255–261.

Stellefson, M., Chaney, B., Barry, A. E., Chavarria, E., Tennant, B., Walsh-Childers, K., et al. (2013). Web 2.0 chronic disease self-management for older adults: a systematic review. Journal of Medical Internet Research, 15(2), e35. doi:10.2196/jmir.2439

Vicente, K. (2003). The Human Factor: Revolutionizing the Way People Live With Technology. New York: Routeledge.

Westbrook, J. I., Braithwaite, J., Georgiou, A., Ampt, A., Creswick, N., Coiera, E., & Iedema, R. (2007). Multimethod evaluation of information and communication technologies in health in the context of wicked problems and sociotechnical theory. Journal of the American Medical Informatics Association, 14(6), 746–755. doi:10.1197/jamia.M2462

Wiles, J. L., Leibing, A., Guberman, N., Reeve, J., & Allen, R. E. S. (2012). The meaning of “aging in place” to older people. The Gerontologist, 52(3), 357–366. doi:10.1093/geront/gnr098

Woodend, A. K., Sherrard, H., Fraser, M., Stuewe, L., Cheung, T., & Struthers, C. (2008). Telehome monitoring in patients with cardiac disease who are at high risk of readmission. Heart & Lung : the Journal of Critical Care, 37(1), 36–45. doi:10.1016/j.hrtlng.2007.04.004

Woods, L. W., & Snow, S. W. (2013). The impact of telehealth monitoring on acute care hospitalization rates and emergency department visit rates for patients using home health skilled nursing care. Home Healthcare Nurse, 31(1), 39–45. doi:10.1097/NHH.0b013e3182778dd3

World Health Organization. (2011). Global status report on noncommunicable diseases 2010. Retrieved from: http://apps.who.int/iris/bitstream/10665/44579/1/9789240686458_eng.pdf

SELF-­‐MANAGEMENT  &  INFORMATICS           16