Interoperable and multi-fow software environment:application to Health Care Supply Chain

Pierre Féniès, Michel Gourgand, Sophie Rodier

LIMOS CNRS UMR 6158Campus des Cézeaux, 63173 Aubière, France

{fenies, gourgand, rodier}@isima.fr

Abstract. In this paper, we propose a generic decisional model allowing toevaluate in a total way (physical fows, fnancial fows) plannings for anysystem contained in supply chain. We present a methodology for decision-making aid software conception. This methodology use modelling andsimulation concept and show the interest of going towards Advanced Budgetingand Scheduling software for complexes supply chains performance evaluation.To show the generic character of the decisional approach, we apply the chainingof models suggested to the logistic process of Health Care Supply Chain. Wegive the metrics resulting from the modelling and the simulation of the patienttreatment in the Hospital system.

Keywords: APS, ABS, Multi fow software environment, interoperability.

1 Introduction

Hospital system is an opened system which interacts with external logistic entities ormedical service providers. The comparison with industrial supply chain is obvious:the current hospital, taking into account its growing complexity, is closer to animmense logistic chain whose agents aim at satisfying patients. So, Health CareSystems can be seen as a Health Care Supply Chain (HSC) [1]. As medical organizations grow, information fow managing between variouscomponents becomes more complex. Health management is a knowledge intensiveactivity and most organizations have specialist sub-domains, each with its ownvocabulary, knowledge base and software applications. The fact that these sub-domains contain multi-platform, multi-vendor application wrappers built aroundmulti-variate data sources further adds to the complexity [2].So HSC information system needs can be compared with industrial Supply Chaininformation system needs with regard to data integration and interconnection.Then, as [3] show it, interoperability appears to be a major approach for the design ofapplications dedicated to access information. The Supply Chain manager has topossess a set of tools and methods capable of helping him in design problems as inpiloting problems but also capable of furthering interoperability of informationsources. In fact, decision-making aid software depend increasingly on variousheterogeneous resources, such as databases, knowledge bases, fles, Web-basedinformation, and so on. Moreover, the complexity of a HSC, as of industrial SupplyChain, is due to the structure of the logistic process [4] and to the number of entitieswhich interact simultaneously.

The purpose of this article is to propose an interoperable and multi-fow softwareenvironment for HSC which combines simulation and performance evaluation and toconnect this decision-making aid software with HSC information system. One of theobjectives of this work will be the integration of a decisional and fnancial applicativebrick in the APS (Advanced Planning Scheduling). In fact, thanks to the analysis ofexisting tools and methods [5] we will show that the latter don’t integrate in theirdecisional approach, in intra-organisational context as in inter-organisational context,the constraints evaluation resulting from fnancial fow. If decision-making aid toolstry to improve the organization proftability by improving a number of physical fowperformance criteria, they don't interpret, or inadequately, the physical fow elementsin fnancial fow elements translation.

Fig. 1. Financial unit integration in software suite of APS type for the Supply Chain

This paper is organized as follows: in next section, a state of the art about integrateddecision-making aid software concept and a brief state of decision-making aidsoftware market are given. An interoperable and multi-fow decision-making aidsoftware suite is proposed in section 3. Section 4 is dedicated to the presentation of astudy case. Finally, conclusion and future research work are presented.

2 State of the art

In this section, we present a brief state of the art on the necessity of an integratedinformation system for Supply Chain and Health Care Supply Chain, and in a secondpart, we briefy compare some decisional tools applicable to Health Care system.

2.1. Necessity of integrated decision-making aid software

In a literature review [5] show that enterprises have to implement inter-organizationalintegration due to increasing competition and globalization. This integration is thenused as basis for a transparent inter-organizational integration of all members of thewhole supply network allowing a continuous exchange of information between themembers. Company-internal integration seems to be a precondition for an inter-organizational integration. [6] show that it is possible to integrate and access various

heterogeneous information sources within a hospital Intranet based on the ARIANEarchitecture and the Unifed Medical Language System (UMLS) ontology. Theirprototype demonstrates the interest of this common ontology when associated withthe Information Source MAP (ISM) [7] which provides with a catalogue of existingservers. The use of ontologies to provide interoperability among heterogeneous datasources has been applied in many domains including manufacturing [8] and medicalinformation systems [9,10]. In a literature review about cost models, [11] shows thatActivity Based Costing (ABC) system is the best type of cost model for complexsystem because of its connections with Supply Chain management. As shown by [12],integrating fnancial fow and physical fow in Supply Chain management is essentialto optimize fnancial fow and we think that there is a need for a general approach forboth Supply Chain modelling and its evaluation which combines physical andfnancial fows thanks to ABC. [13] show that there is not in literature approacheswhich propose to combine physical fow simulation, fnancial fow evaluation anddata integration.

2.2 Existing software for decision-making about fow

Nowadays the effective decision-making importance grows and many tools were setup on the market in order to answer this request. Information to be presented at theuser is the central problems of any decisional project. The decisional tools aim toallow consolidations establishment and to bring closer data, primarily at ends ofreporting or decision-making. They are data consultation tools, on variablesaggregation or detail levels, and also observed according to variable axes (forexample: to measure the costs, the sales or proftability, by geographical area,temporal period or product range). The decisional tools market counts a certainnumber of solutions as regards Cost Accounting and Budgetary Development. Table 1retains some software packages, some specialized enough, others generic, which arecompared on various criteria. Our study is not exhaustive, and we have only studiedthe most important editors which propose integrated solutions. For each APS, westudy if fnancial fow is integrated, for example with credit management functions, ifcosting management models are implemented, and if scorecards with fnancialsmetrics are used. This analysis shows that in network confguration, the optimizationis done with very simple costs constraints. But in tactical or operational activities,fnancials constraints are not integrated and are not evaluated. Note that some of thetested APS have links with ERP (for example APO and R3 which are edited by SAP),but these links don’t integrate fnancial evaluation with planning. Moreover, note thatdiscrete event simulations are not used by APS, which only use optimization.

Table 1. Encompassing view of various tools functionalities

DatawareHouse

ProcessModelling

Physicalfow Opti-mization

BudgetaryDevelop-

ment

Discreteevent

Simulation

Not specialized toolsADEXA iCollaboration Suite ; ASPENeSupply Chain Suite ; FUTURMASTERFuturmaster; ORACLE aps; PEOPLESOFT SupplyChain Planning; SAPAdvanced Planer and Optimization (APO);SYNQUEST One2One Solutions.

NotSpecifed

Yes Yes No No

"Health" specialized tools SIB Sextant; KEYRUS K@-prim; MCKESSON Evoluance SIAD

NotSpecifed

Yes Notspecifed

Yes No

Moreover, to avoid high maintenance costs or to deploy a standard corporate model inan international group, some corporations are implementing ERP systems without orwith minimal customization or interoperability [14].We conclude that if HSC manager want to plan and budget the hospital activities as awhole they must use software which permit a real integration of Supply Chaininformational, physical and fnancial fows in decision making process. This type ofsoftware does not actually exist. We propose in next section a type of software whichtakes into account physical and fnancial fows thanks to decision making tools andinformation fow thanks to data warehouse in planning and budgeting activities.

3 Proposal of an interoperable and multi-fow decision-making aidsoftware suite

It is worth noting that there is a need for a general approach for both HCS modellingand its evaluation which combines data from physical, informational and fnancialfows in one type of software which is a global Advanced Planning and Scheduling(APS) [15]. This one allows solving HCS problem with an integration of all thesystem fow. We call Advanced Budgeting and Scheduling (ABS) this type of APSwhich combines all the fows and integrates data from the information system. First, we propose in this section the ASDI-HSC environment, which means Analysis,Specifcation, Design, and Implementation for the systems of the Health Care SupplyChain class. In a second time, we present the concept of ABS which is made thanks toASDI-HSC environment.

3.1 Environment for a multi-fow tool design

We use a methodology called ASDI (Analysis, Specifcation, Design, andImplementation) [16] dedicated to the design and the implementation of modelling,simulation and piloting software environments for a domain.

Modelling software environment ASDI-HSC Modelling environment

Fig. 2. ASDI-HSC environment

Figure 2 only presents the visible elements for the manager. These elementscommunicate using the interfaces layer. The environment corresponds to the conceptof software engineering workshop for the Supply Chain modelling and performanceevaluation, whether this one is centred production of goods or services. The ASDI-HSC environment makes it possible to design and establish software suite of ABStype (Advanced Budgeting and Scheduling) which constitutes an evolution in thedecision-making aid tools for Supply Chain. ASDI-HSC includes:- a performance evaluation system, core of the environment; the performanceevaluation layer allows the one or more action models development according to themodelling objectives. SIMAN V and WITNESS are indifferently used as core of thissoftware environment. PREVA (PRocess EVAluation) approach [20] thus allows tothe action models constitution whose objectives are centred on the value creation, butalso on "patient" satisfaction;- a metric selection part, consisted by SCOPE approach (Supply Chain OperationalPerformance Evaluation)[1] which allows the balanced scorecards construction andestablishment for the behaviours orientation in HSC.- a data warehouse which allows the access to data necessary to the tools belonging tothe various part of the environment ;- an operational research part which uses Mixed Integer linear Programs (MILP) (Foroperating theatre…).- a statistical part, which allows the analysis and the processing the existing data(forecasts of load, learning curves) as well as the study of the results obtained by thecore of the environment.- Graphics tools and 3D emulation which makes possible to animate in 3D withMANTRA 4D the simulation models. This three-dimensional chart tool is verysignifcant to imply the actors in the organizational change.- a part which contains methods of analysis and specifcation. ARIS and UML toolsare here used as formalisms and methods for specifcation.- a modelling methodology of the feld which was presented in [13], [16].

3.2. ASDI-HSC environment use for an Advanced Budgeting and Schedulingsoftware design

Figure 3 shows the characteristics of an ABS and the existing connections betweenthe various activities of Supply Chain physical and fnancial fows, the modellingapproaches and the decisional horizons interacting with the various data-processingand mathematical models included in ABS.

Fig. 3. An Advanced Budgeting and Scheduling software

Supposing that the activity "to budget for" for fnancial fow is the equivalent of theactivity "to plan it" for physical fow, we defne Advanced Budgeting and Schedulingas a coherent succession of software applications allowing the optimization and theperformance evaluation of supply chain physical and fnancial fows and combiningoverall (for the whole of the chain) like locally (for an entity) the strategic, tactical,operational decisional horizons [17] with macroscopic, mesoscopic and microscopicmodelling approaches. These various applications are connected to the informationsystem of supply chain entities by a data warehouse which reprocesses heterogeneousdata resulting from different software applications to feed in information theprescriptive models like descriptive contained in ABS. Usually, prescriptive models[18] are used for decision-making: they are used to make a choice on the design,control and the functioning of supply chain [19], while the descriptive models [19]make it possible to evaluate the decisions made by the prescriptive model or directlyby the actors. Technical and conceptual features of an ABS are given in table 3 which shows thepassage from an APS software suite to an ABS software suite. If the context of use ofan ABS is the same one (internal Supply Chain as well as external) as an APS, thesoftware functionalities integrate planning and budgeting of the activities (forexample, choice of the planning which generates the maximum of cash-fow) and themeasuring tools of the performance use concepts more advanced than the fewindicators of physical fow. This type of software suite can be used for a complexsystem of the Supply Chain as for the whole Supply Chain. We integrate in ABS adecisional module which organizes information for Supply Chain managers in theform of prospective scorecard for the ex ante activities evaluation.

Table 3. Transition from an APS to an ABS

Advanced Planning and Scheduling [15] Advanced Budgeting and Scheduling

Context Internal and external Supply Chain Internal and external Supply ChainFunctionalities

Network DesignDistribution (DRP)Production (PDP)Supplying (MRP)Scheduling and transport

For physical fowFor physical fowFor physical fowFor physical fowFor physical fow

For physical and fnancial fowsFor physical and fnancial fowsFor physical and fnancial fowsFor physical and fnancial fowsFor physical and fnancial fows

Decisional ToolsPerformance Measurement Some physical fow metrics Balanced Scorecard+ PREVA model

[16]

Connection with the chainentities information

systemNot detailed

Data warehouses allowing collection ofdata and information from heterogeneous

applicationsSoftware components for

decision making tools Optimisation (Cplex) and heuristics Coupling of optimisation/ simulation(prescriptive and descriptive models)

Collaborative Planning

Collaborative planning gives to the chainentities the quantity of products and

services to be produced and delivered onshort, medium and long term for a given

customer satisfaction rate.

Collaborative planning gives to the chainentities the quantity of products and

services to be produced and delivered onshort, medium and long term which gives

the highest level of value for Supply Chainentities.

The supply of the centred part on the costs and the fnancial part of the prospectivescorecard is carried out by the model PREVA [20] which makes it possible to translatein a prospective and causal way the impact of physical fow into element of fnancialfow by a succession of Activity Based Costing models. PREVA evaluate in themedium and long term cash fows generated by Supply Chain and the entities whichmake it up, but also in the short time the position of treasury of the Chain entitiesgenerated by a collaborative planning.In the APS, the interfacing with each entity information system which makes it up isnot carried out. We propose to carry it out in ABS by a data warehouse which allowsthe collection and the data securisation resulting from heterogeneous applications.Lastly, collaborative plannings of the APS are oriented Patient or CustomerSatisfaction (with the logistic meaning of the term) and do not integrate the valuecreation concept for the actors who take part in the network Supply Chain.Collaborative plannings resulting from an ABS allow, for a level of customersatisfaction given to choose the solution which generates the most value for the wholeof the chain actors and to design the division of the latter.

4. Application

The generic evaluation model presented previously was applied to a real HSCapplication. This application is done in collaboration with AXEGE society. In thisHSC several cares are done far away the Hospital, for example in the laboratory or inimagery. In hospitals, there is a lot of units which are very often saturated and can’ttreat all the patients which are addressed to them. The objective of this study is toevaluate, according to physical and fnancial criteria, various rules of patients priorityin the context of systems of health regulation mechanism. For that, the environmentpreviously presented is implemented. In a frst paragraph, we present briefy the studycase, giving the details of the modelling process, while the second paragraph presentsthe simulation results which come from the HSC modelling and simulation. Note thatmany processes are evaluated in the case study and different granularity levels aremodelled and evaluated.

4.1. Action model modelling and development

HSC modelling is given on fgure 4. Figure 5 shows the links between softwareapplications, information fows, fnancial fows and physical fows in order to make adecision making aid tool.We present here an example of application of the decision making aid tool proposed.For the work of modelling and data collection was carried out in collaboration withthe Hospital. In the study case, a priority is associated to each treatment. Indeed, themanagement of the priorities is as follows: an agenda for patient appointment date ismade for each day. This last one is elaborated by supposing a processing time of theaverage patient without taking into account his pathology and its severity. In addition,any patients coming from other departments must be also treated. It is then possiblethat some schedules patients are not treated the right day. Pathologies differ accordingto their severity, their medical resources consumption and their remuneration. Theobjectives of the HSC being multiple (proftability, treatment rate...), the choice of apatients treatments priority rule is complex. We suppose that physical fow iscomposed of patients fow. Figure 5 presents a chain of patient treatment process in ahospital. It is important to specify that the various interventions are not inevitablycarried out within the hospital, indeed the laboratory is for example located onanother site. A simulation model under SIMAN V Arena of this system was developedin order to evaluate in a stochastic context the best rule of patients prioritymanagement.Five priority rules (heuristic) are evaluated as follows: • H1: First patient check-in, frst patient treated (current rule). • H2: The largest criterion of severity (for equivalent criterion of severity, FIFO).• H3: The largest fnancial criterion (for equivalent criterion of severity, the fnancialcriterion the most interesting fnancial criterion). • H4: Processing time considered on average shortest (with criterion of equivalenttime, frst in, frst out).• H5: The longest processing time (with criterion of equivalent time, frst in, frst out).In the case of identical criterion, rule FIFO is applied.

Fig. 4. Event Process Chain of the patient way in the Hospital.

Fig .5. Links between software applications and fows in real case study

This simulation is not determinist and fnishing. Six families of pathologies: P1 to P6are considered. The patients check-in follows an exponential law of average 15 mm.The pathologies distribution and the processing time of pathologies by the medicalresources are given by table 4. The criterion of pathology severity does notcorrespond to an emergency criterion. The fnancial data are "pro format" and arebuilt starting from a regulation system for public health care system. Figure 6represents the translation of specifcation model previously defned into simulationmodel with Arena tool. To realize the simulation of the HSC on 365 days, a time of 15minutes is necessary.

Table 4. Initial data.

P1 P2 P3 P4 P5 P6Distribution law Seasonality of pathologiesProcessing following a normal distribution

N(14,2) N(15,5) N(21,5) N(25,5) N(15,5) N(20,2)

Severity (of the least serious to the most serious)

1 2 3 3 2 2

Pathology price (€) 20 17 22 30 15 25Pathology margin (€) 10.62 8.75 6.5 7.98 8.8 8.37

Output variables to observe are: the annual average number of patients treated bypathology, the annual rate of patients satisfaction, the annual rate of medical resourcesoccupation. Input Variables are: Priority rules. Initial state of the system: the HospitalSupply Chain resources are free and the waiting rooms are empty at the beginning ofeach simulated day. Finishing conditions of the simulation: one day which issimulated begins at 8 AM and fnishes at 6 PM. Collect results are: a replicationconsists of 365 days consecutive without restoring of the "laws". We made 30 replicasof 365 days and determine the average value of each observable variable. Theobserved variables of the patients treatment of the HSC are then used by thedecisional module resulting from PREVA.

4.2 Results

The analysis of the physical fow results is carried out using the approach for fnancialperformance evaluation (PREVA). This tool treats the data, which it receives from thesimulation model. This data are exported from SIMAN V Arena tool to Scorecards,using the Visual Basic language. Thus starting from the physical fows represented inthe simulation model we have the translation of corresponding fnancial fows. Theinput data of decisional model detailed previously and which are provided at the endof the simulation are the annual number of patients treated by pathology, the numberof patients untreated by pathology, as well as the use ratio of medical resources.Finally, the tool for performance evaluation enabled us to obtain results for eachevaluated management rule, these results are represented on fgure 6. The analysis ofthe results (table 5) makes it possible to initially show the sensitivity of theperformances indicators compared to various management rules of treatment prioritybut also to select the best rules for the analyzed system.

Table 5. Selection of management rules

Management Rule H2 H3 H4 H5A number of patients sol < H1 sol >H1 Best rule sol < H1Satisfaction Patients sol < H1 sol >H1 Best rule sol < H1Resources use id H1 id H1 id H1 id H1Value Creation sol < H1 Best rule sol >H1 sol < H1Generated Cash lows sol < H1 Best rule sol >H1 sol < H1

Selection eliminated H3 & H4 better than H1 eliminated

Fig. 6. Results

The decisional approach gives criteria of selection which allow, for an equivalent orhigher quality of "patient satisfaction", to select the most advantageous rules ofmanagement on the fnancial. If the results presented validate the decisional approach,the various rules of management and their order are relevant only compared to thecase study

5. Conclusion

We proposed a modelling environment for Supply Chains class systems. Thissoftware environment, based on ASDI modelling process has for objective to help theexperts in modelling and the managers to model a complex system such as a HSC. Weintegrated in this context the evaluation constraints resulting from fnancial fows andpropose new decisional software called ABS, which permits the taking into account ofperformance evaluation methods in interdisciplinary and interoperable context ofSupply Chain management. Thanks to this approach, we are able to connect decisionmaking tools using simulations for all the fows (physical, fnancial and informationalfows)/ This approach is validated in a health care supply chain (with different entitiessuch as laboratories, internal and external unit of care). This generic approach enablesus to consider, in a next study, the integration of ABC model and fnancial fows inoptimization models in order to improve running of HSC. We also wish to propose anextension of this approach in large external Supply Chain in order to improve theirfunctioning and to allow the managers to share the value creation realized bycollaborative planning and to develop interoperability in intra-organizational as ininter-organizational context for other types of supply chain (industrial …).

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