Address correspondence to Jeanne S. Ringel, Ph.D., RAND Corporation, 1776 Main Street, PO Box 2138, Santa Monica, CA 90407; e-mail: firstname.lastname@example.org. Christine Eibner, Ph.D., is with the RAND Corporation, Arlington, VA. Jeanne S. Ringel, Ph.D., Federico Girosi, Ph.D., Amado Cordova, Ph.D., and Elizabeth A. McGlynn, Ph.D., are with the RAND Corporation, Santa Monica, CA.
Modeling Health Care Policy Alternatives
Version of Record online: 2 AUG 2010
© Health Research and Educational Trust
Health Services Research
Volume 45, Issue 5p2, pages 1541–1558, October 2010
How to Cite
Ringel, J. S., Eibner, C., Girosi, F., Cordova, A. and McGlynn, E. A. (2010), Modeling Health Care Policy Alternatives. Health Services Research, 45: 1541–1558. doi: 10.1111/j.1475-6773.2010.01146.x
- Issue online: 9 SEP 2010
- Version of Record online: 2 AUG 2010
- health care policy
Background. Computer models played an important role in the health care reform debate, and they will continue to be used during implementation. However, current models are limited by inputs, including available data.
Aim. We review microsimulation and cell-based models. For each type of model, we discuss data requirements and other factors that may affect its scope. We also discuss how to improve models by changing data collection and data access procedures.
Materials and Methods. We review the modeling literature, documentation on existing models, and data resources available to modelers.
Results. Even with limitations, models can be a useful resource. However, limitations must be clearly communicated. Modeling approaches could be improved by enhancing existing longitudinal data, improving access to linked data, and developing data focused on health care providers.
Discussion. Longitudinal datasets could be improved by standardizing questions across surveys or by fielding supplemental panels. Funding could be provided to identify causal parameters and to clarify ranges of effects reported in the literature. Finally, a forum for routine communication between modelers and policy makers could be established.
Conclusion. Modeling can provide useful information for health care policy makers. Thus, investing in tools to improve modeling capabilities should be a high priority.