Dynamic microsimulation models for health outcomes: a review.

BACKGROUND

Microsimulation models (MSMs) for health outcomes simulate individual event histories associated with key components of a disease process; these simulated life histories can be aggregated to estimate population-level effects of treatment on disease outcomes and the comparative effectiveness of treatments. Although MSMs are used to address a wide range of research questions, methodological improvements in MSM approaches have been slowed by the lack of communication among modelers. In addition, there are few resources to guide individuals who may wish to use MSM projections to inform decisions.

METHODS

. This article presents an overview of microsimulation modeling, focusing on the development and application of MSMs for health policy questions. The authors discuss MSM goals, overall components of MSMs, methods for selecting MSM parameters to reproduce observed or expected results (calibration), methods for MSM checking (validation), and issues related to reporting and interpreting MSM findings(sensitivity analyses, reporting of variability, and model transparency).

CONCLUSIONS

. MSMs are increasingly being used to provide information to guide health policy decisions. This increased use brings with it the need for both better understanding of MSMs by policy researchers, and continued improvement in methods for developing and applying MSMs.