Markov Modeling & Discrete Event Simulation in Health Care: Systematic Comparison
2014
This review assesses whether the use of Markov modeling (MM) or discrete event simulation (DES) for cost-effectiveness analysis (CEA) may alter healthcare resource allocation decisions. A systematic literature search and review of empirical and non-empirical studies comparing MM and DES techniques used in the CEA of healthcare technologies was conducted.
The primary advantages described for DES over MM were the ability to model queuing for limited resources, capture individual patient histories, accommodate complexity and uncertainty, represent time flexibly, model competing risks, and accommodate multiple events simultaneously. The disadvantages of DES over MM were the potential for model overspecification, increased data requirements, specialized expensive software, and increased model development, validation, and computational time.
The authors conclude that where individual patient history is an important driver of future events, an individual patient simulation technique like DES may be preferred over MM. Where supply shortages, subsequent queuing, and diversion of patients through other pathways in the healthcare system are likely to be drivers of cost-effectiveness, DES modeling methods may provide decision makers with more accurate information on which to base resource allocation decisions.
Markov Modeling & Discrete Event Simulation in Health Care: Systematic Comparison
Source:
Standfield L, Comans T, Scuffham P. Markov Modeling and Discrete Event Simulation in Health Care: a Systematic Comparison. International Journal of Technology Assessment in Health Care 2014; 30 (2): 165-172. https://doi.org/10.1017/S0266462314000117
Not open access.