Discrete Event Simulation: The Preferred Technique for Health Economic Evaluations?

Authors


Jaime Caro, 430 Bedford Street, Lexington, MA 02420, USA. E-mail: jaime.caro@mcgill.ca

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.

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