In cases in which different dynamic simulation modeling methods may be used for the health care delivery problem, several specific elements were identified for differentiating the methods such as the perspective, the origin of dynamic interactions in the system, and resource requirements in terms of manpower and costs. This report builds on this work by systematically comparing each of these three dynamic simulation modeling methods, and by identifying criteria for selecting the most suitable method among these three alternative methods depending on the type of problem being addressed. The SIMULATE checklist identifies eight elements (System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence) that characterize problems that could be addressed more effectively using dynamic simulation modeling methods rather than other modeling methods. Finally, the System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence (SIMULATE) checklist was developed and presented as a tool to help researchers decide whether dynamic simulation modeling is an appropriate method for modeling the effects of a particular policy or health care intervention on a health care system. The article introduced three dynamic simulation modeling methods most commonly used-system dynamics (SD), discrete-event simulation (DES), and agent-based modeling (ABM)-and reviewed where they differ from models more typically used in economic evaluation such as Markov models and decision trees. ], the ISPOR Task Force on Dynamic Simulation Modeling Applications in Health Care Delivery Research Emerging Good Practices introduced the fundamentals of dynamic simulation modeling by defining complexity and health care systems interventions and identifying the types of health care delivery problems for which dynamic simulation modeling can be used. The report directs readers to other resources for further education on these individual modeling methods for system interventions in the emerging field of health care delivery science and implementation.

Upon reviewing this report in addition to using the SIMULATE checklist, the readers should be able to identify whether dynamic simulation modeling methods are appropriate to address the problem at hand and to recognize the differences of these methods from those of other, more traditional modeling approaches such as Markov models and decision trees. This report provides an overview of these modeling methods and examples of health care system problems in which such methods have been useful. The primary aim of the report was to aid decisions as to whether these simulation methods are appropriate to address specific health systems problems.

We review criteria for selecting the most suitable method depending on 1) the purpose-type of problem and research questions being investigated, 2) the object-scope of the model, and 3) the method to model the object to achieve the purpose. Finally, we provide guidance for emerging good practices for dynamic simulation modeling in the health sector, covering all aspects, from the engagement of decision makers in the model design through model maintenance and upkeep. We conclude by providing some recommendations about the application of these methods to add value to informed decision making, with an emphasis on stakeholder engagement, starting with the problem definition. Finally, we identify areas in which further methodological development will likely occur given the growing “volume, velocity and variety” and availability of “big data” to provide empirical evidence and techniques such as machine learning for parameter estimation in dynamic simulation models.

This report builds on the previous work, systematically comparing each of the three most commonly used dynamic simulation modeling methods-system dynamics, discrete-event simulation, and agent-based modeling. In a previous report, the ISPOR Task Force on Dynamic Simulation Modeling Applications in Health Care Delivery Research Emerging Good Practices introduced the fundamentals of dynamic simulation modeling and identified the types of health care delivery problems for which dynamic simulation modeling can be used more effectively than other modeling methods. The hierarchical relationship between the health care delivery system, providers, patients, and other stakeholders exhibits a level of complexity that ought to be captured using dynamic simulation modeling methods. As a tool to help researchers decide whether dynamic simulation modeling is an appropriate method for modeling the effects of an intervention on a health care system, we presented the System, Interactions, Multilevel, Understanding, Loops, Agents, Time, Emergence (SIMULATE) checklist consisting of eight elements.

Albuquerque journal delivery problem