Modeling and simulation framework for value-based healthcare systems. (June 2019)

• Record Type: Journal Article
• Authors: Traoré, Mamadou Kaba; Zacharewicz, Gregory; Duboz, Raphaël; Zeigler, Bernard
• Is Part Of: Simulation. Volume 95:Number 6(2019)
• Page Start: 481
• Page End: 497
• Publication Date: 2019-06
• Subjects: Value-based healthcare system -- healthcare modeling and simulation -- holistic analysis -- model integration -- experimental frame; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549718776765
• Languages: English
• ISSNs: 0037-5497

Abstract

Regardless of the coordination of its activities, a healthcare system is composed of a large number of distributed components that are interrelated by complex processes. Understanding the behavior of the overall system is becoming a major concern among healthcare managers and decision-makers. This paper presents a modeling and simulation framework to support a holistic analysis of healthcare systems through a stratification of the levels of abstraction into multiple perspectives and their integration in a common simulation framework. In each of the perspectives, models of different components of a healthcare system can be developed and coupled together. Concerns from other perspectives are abstracted as parameters, that is, we reflect the parameter values of other perspectives through explicit assumptions and simplifications in such models. Consequently, the resulting top model within each perspective can be coupled with its experimental frame to run simulations and derive results. Components of the various perspectives are integrated to provide a holistic view of the healthcare problem and system under study. The resulting global model can be coupled with a holistic experimental frame to derive results that cannot be accurately addressed in any of the perspectives taken alone. Furthermore, as we endeavored to allow perspective-specific experts to contribute to the modeling process, we took benefit of results originating from research efforts that Norbert Giambiasi initiated in the 2000s, which his PhD students further developed with their own PhD students.