Tuesday, January 7, 2014
Poster Board # P2-33

Beate Jahn, PhD1, Ursula Rochau, MD, MSc2, Christina Kurzthaler, Bsc3, Martina Kluibenschaedl, Bsc.1, Christoph Urach4, Patrick Einzinger, MSC5, Harald Piringer, Msc6, Niki Popper, MSc5 and Uwe Siebert, MD, MPH, MSc, ScD7, (1)UMIT - Institute of Public Health, Medical Decision Making and HTA, Hall in Tyrol, Austria, (2)UMIT - Institute of Public Health, Medical Decision Making and HTA/ ONCOTYROL - Area 4 HTA and Bioinformatics, Hall in Tyrol/ Innsbruck, Austria, (3)Institute of Public Health, Medical Decision Making and HTA, Hall in Tyrol/ Innsbruck, Austria, (4)Vienna University of Technology, Vienna, Austria, (5)Dwh Simulation Services, Vienna, Austria, (6)VRVis Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH, Vienna, Austria, (7)UMIT/ ONCOTYROL/ Harvard School of Public Health/ Harvard Medical School, Hall, Austria
Purpose: Discrete-Event-Simulation (DES) is a commonly used modeling tool to analyze the comparative effectiveness of alternative health technologies and to optimize resource allocation in healthcare settings. DES models are often rather complex and visualization is used for the conceptual model, to support programming (i.e. visual programming languages (VPL)) and to display the results. This study aims to provide a comprehensive overview of visualization techniques that are currently used in different fields.

Method: Visualization methods and their applications in healthcare, engineering, and operations research were sought from a wide variety of sources, including literature databases (e.g. PubMed) and webpages of simulation conference (e.g. WSC), academic societies and further publications (e.g. FIPS PUBS).  The literature review focused on model conceptualization and programming, and presentation of the results.

Result: For depicting the conceptual model, visualization methods such as event graphs, activity diagrams, IDEF (Integration DEFinition) diagrams, process-flow diagrams, or petri nets were used in engineering and operations research. For example, event-graph diagrams are well suited for simple problems. However, interactions between individuals (e.g. queues), resources and decisions are not made explicit. Therefore, more elaborated techniques such as IDEF diagrams or process-flow diagrams are applied. The recently published ISPOR-SMDM Modeling Good Research Practice guidelines recommend flow diagrams or state charts to represent the key elements of a model, including the possible pathways, and the presence of queues and decision points. Flow diagrams seem to be a good form of visualization that is also applied to support programming within VPLs and software. However, for illustrating concepts such as the natural history of a disease in a decision-analytic model, a how-to guidance would be helpful. In addition, animated representation of a DES is recommended for engaging the model users and to support model debugging. Results of a DES model can be presented in commonly used formats in HTAs and cost-effectiveness studies (e.g., tables or cost-effectiveness plane).

Conclusion: There exist several visualization techniques for the three different purposes: conceptualization, programming and representation of the results. For reporting the results, standard methods used in HTA can be applied also for DES models. Flow diagrams are well suited for model conceptualization and programming purposes. Future studies are warranted for further specification and standardization of visualization methods to be used in DES studies in healthcare.