Analyzing national health reform strategies with a dynamic simulation model

Abstract

Proposals to improve the US health system are commonly supported by models that have only a few variables and overlook certain processes that may delay, dilute, or defeat intervention effects. We use an evidence-based dynamic simulation model with a broad national scope to analyze 5 policy proposals. Our results suggest that expanding insurance coverage and improving health care quality would likely improve health status but would also raise costs and worsen health inequity, whereas a strategy that also strengthens primary care capacity and emphasizes health protection would improve health status, reduce inequities, and lower costs. A software interface allows diverse stakeholders to interact with the model through a policy simulation game called HealthBound.

FIGURE 1

Connections between the major elements of a simulated US health system model. Note. The following elements are stratified by socioeconomic status: behavioral risks, environmental hazards, health status, type and locus of care received, primary care providers, access, insurance coverage, and cost sharing. For detailed explanation of the relationships among the elements, see the technical appendix (available as a supplement to the online version of this article at http://www.ajph.org).

FIGURE 2

Outcomes in model simulating the US health system, by scenario for (a) per capita costs, (b) quality-adjusted life-years (QALYs), and (c) net benefit. Note. The change in per capita costs equals the change in health care costs plus spending on intervention programs. The change in QALYs results from fewer deaths plus fewer unhealthy days. Net benefit is calculated as the product of the change in QALYs × $75 000 minus the change in costs. All 3 measures are presented here on a per capita basis, using total population as the denominator. All outcomes shown are computed according to the baseline parameter setting.