Published Jun 2015
Marshall DA, Burgos-Liz L, IJzerman MJ, et al. Applying dynamic simulation modeling methods in health care delivery research—the SIMULATE checklist: report of the ISPOR Simulation Modeling Emerging Good Practices Task Force. Value Health. 2015;18(1):5-16.
Health care delivery systems are inherently complex, consisting of
multiple tiers of interdependent subsystems and processes that are
adaptive to changes in the environment and behave in a nonlinear
fashion. Traditional health technology assessment and modeling
methods often neglect the wider health system impacts that can be
critical for achieving desired health system goals and are often of
limited usefulness when applied to complex health systems.
Researchers and health care decision makers can either underestimate
or fail to consider the interactions among the people, processes,
technology, and facility designs. Health care delivery system interventions
need to incorporate the dynamics and complexities of the
health care system context in which the intervention is delivered.
This report provides an overview of common dynamic simulation modeling methods and examples of health care system interventions in which such methods could be useful. Three dynamic simulation modeling methods are presented to evaluate system interventions for health care delivery: system dynamics, discrete event simulation, and agent-based modeling. In contrast to conventional evaluations, a dynamic systems approach incorporates the complexity of the system and anticipates the upstream and downstream consequences of changes in complex health care delivery systems.
This report assists researchers and decision makers in deciding whether these simulation methods are appropriate to address specific health system problems through an eight-point checklist referred to as the SIMULATE (System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence) tool. It is a primer for researchers and decision makers working in health care delivery and implementation sciences who face complex challenges in delivering effective and efficient care that can be addressed with system interventions.
On reviewing this report, the readers should be able to identify whether these simulation modeling methods are appropriate to answer the problem they are addressing and to recognize the differences of these methods from other modeling approaches used typically in health technology assessment applications.
Keywords: decision making, dynamic simulation modeling, health care delivery, methods.
Copyright © 2015, International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc.