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GMDS 2012: 57. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS)

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

16. - 20.09.2012, Braunschweig

Hybrid simulation as tool for prospective assessments of healthcare technology

Meeting Abstract

  • Anatoli Djanatliev - Universität Erlangen-Nürnberg, Deutschland
  • Peter Kolominsky-Rabas - Universität Erlangen-Nürnberg, Deutschland
  • Bernd M. Hofmann - Siemens AG, Healthcare Sector, Clinical Competence Center Neuroscience, Deutschland
  • Reinhard German - Universität Erlangen-Nürnberg, Deutschland

GMDS 2012. 57. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS). Braunschweig, 16.-20.09.2012. Düsseldorf: German Medical Science GMS Publishing House; 2012. Doc12gmds222

doi: 10.3205/12gmds222, urn:nbn:de:0183-12gmds2228

Veröffentlicht: 13. September 2012

© 2012 Djanatliev et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.de). Er darf vervielfältigt, verbreitet und öffentlich zugänglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.


Gliederung

Text

Introduction: Prospective Health Technology Assessment (ProHTA) is an approach that allows improving new healthcare innovations early before the development and design phase has started [1]. One can learn about the impacts of a new technology and it is possible to optimize healthcare processes prospectively. Simulation has been selected to be an appropriate tool to answer the questions which are posed within the scope of ProHTA. On the one hand, there are global and more general impacts (e.g. effects of a new innovation on money budgets), on the other hand detailed workflows and individual effects are considered (e.g. specialized treatment steps, patient’s health state).

Methods: We selected the System Dynamics (SD) approach [2] as modeling tool for global and more aggregated contexts. The Agent-Based Simulation (ABS) is used to simulate patient’s individual workflows and behavior.

According to a conceptual model that was developed by an interdisciplinary co-working [3], the overall simulation has been divided into modules to allow reusability and to master the complexity. Furthermore, it aims to create models in a more generic way.

There are already many examples for hybrid simulation use-case studies in healthcare [4], [5]. To cover all requirements of ProHTA, we developed a common hybrid simulation environment that is based on the Process Environment Format, published by Chahal and Eldabi [6]. This allows distinguishing between the core simulation which is modeled by the ABS approach for the greater part, and the SD environment surrounding it.

All model parts are running parallel from each other and continuous SD modules are loosely coupled with discrete ABS ones by annual synchronization. This helps to minimize performance losses during simulation runs.

Results: Two German research groups [7], [8] developed prototypes of Mobile Stroke Unit (MSU) and Stroke-Einsatz-Mobil (STEMO). The idea is to transfer the extremely time-critical thrombolytic therapy to the pretreatment phase by applying a Computer Tomography (CT) and necessary laboratory analyses onsite at stroke occurrence location.

We implemented an MSU use-case scenario as proof-of-concept in order to evaluate our hybrid simulation approach. Statistical data of Berlin were used to reproduce a regional district distribution of the population. In case of affection a patient can call the rescue service that decides, whether a Mobile Stroke Unit can be sent or if there are no free MSUs available.

We used the simulation tool AnyLogic [9] which enables to create multi-paradigm simulation models in one simulation environment. Two simulation runs have been applied to make the effects of MSU implementation visible. After usage of MSUs we could show an exemplary 8% increase of lysed patients.

Conclusions: Hybrid simulation techniques, consisting of SD and ABS models are predestinated to solve problems within the scope of ProHTA. System Dynamics allows to simulate scenarios on a macroscopic level and the Agent-Based approach is used to reproduce patient’s behavior on a behavioral microscopic level.

Acknowledgements: The project Prospective Health Technology Assessment (ProHTA) is funded by the German Federal Ministry of Education and Research (BMBF), project grant No. 01EX1013.


References

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Gantner-Bär M, Djanatliev A, Prokosch HU, Sedlmayr M. Conceptual Modeling for Prospective Health Technology Assessment. In: Proceedings of the XXIV Conference of the European Federation for Medical Informatics. 2012.
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Brailsford SC, Desai SM, Viana J. Towards the holy grail: Combining system dynamics and discrete-event simulation in healthcare. In: Proceedings of the 2010 Winter Simulation Conference; 2010. p. 2293-303.
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Heath SK, Brailsford SC, Buss A, Macal CM. Cross-paradigm simulation modeling: challenges and successes. In: Proceedings of the 2011 Winter Simulation Conference; 2011. p. 2788-802.
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Chahal K, Eldabi T. Applicability of hybrid simulation to different modes of governance in UK healthcare. In: Proceedings of the 2008 Winter Simulation Conference; 2008. p. 1469-77.
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Walter S, et al. Diagnosis and treatment of patients with stroke in a mobile stroke unit versus in hospital: a randomised controlled trial. The Lancet Neurology. 2012.
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Ebinger M, et al. PHANTOM-S: the prehospital acute neurological therapy and optimization of medical care in stroke patients – study. International J Stroke. 2012.
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XJ Technologies Company Ltd. [Internet]. AnyLogic 6. Available from http://www.xjtek.com [cited 23.04.2012] Externer Link