Discrete event simulation: the preferred technique for health economic evaluations?

Abstract

Objectives: To argue that discrete event simulation should be preferred to cohort Markov models for economic evaluations in health care.

Methods: The basis for the modeling techniques is reviewed. For many health-care decisions, existing data are insufficient to fully inform them, necessitating the use of modeling to estimate the consequences that are relevant to decision-makers. These models must reflect what is known about the problem at a level of detail sufficient to inform the questions. Oversimplification will result in estimates that are not only inaccurate, but potentially misleading.

Results: Markov cohort models, though currently popular, have so many limitations and inherent assumptions that they are inadequate to inform most health-care decisions. An event-based individual simulation offers an alternative much better suited to the problem. A properly designed discrete event simulation provides more accurate, relevant estimates without being computationally prohibitive. It does require more data and may be a challenge to convey transparently, but these are necessary trade-offs to provide meaningful and valid results.

Conclusion: In our opinion, discrete event simulation should be the preferred technique for health economic evaluations today.