Using Microsimulation Models to Inform U.S. Health Policy Making

Abstract

Microsimulation models are an important tool for estimating the potential behavioral and economic effects of public policies on decision making units, including individuals and households, employers, suppliers of health insurance and health care services, and government. Among the broader set of models available to researchers and analysts to inform policy decisions, microsimulation models (MSMs) are distinguished from others by their capacity to analyze the policy impact at the level at which it is intended and to incorporate changing behavioral responses and institutional attributes over the time period being assessed (Chollet 1990; Citro and Hanushek 1991). There are four basic components of any MSM: (1) the data infrastructure, (2) behavioral assumptions and parameters, (3) statistical methods, and (4) model output. As its foundation, every MSM must have a core data infrastructure. For many health-related MSMs, the core data file is built using at least one survey or administrative database that contains detailed attributes of individual units within the population. A second component of any MSM is the set of parameters or assumptions pertaining to specific behavioral responses of individuals that would be anticipated as a result of a new policy. Typically, modelers utilize a range of estimates about behavior drawn from the scholarly literature. Modelers then use statistical methods to estimate how changes in behavior due to the policy affect designated outcomes of interest to policy makers. Finally, MSMs produce output summarizing aggregate and in many cases, distributional effects of policy scenarios for a defined population. Recent improvements in data collection, scholarly research evidence, and computing technology over the past two decades have led to the emergence of a new generation of health-related MSMs, including those focusing on health insurance, medical care spending, and population disease burden. Models have been developed and are being used by Federal agencies (e.g., Congressional Budget Office, U.S. Department of Treasury, Centers for Disease Control and Prevention) and private sector entities. Among the latter, MSMs have been developed by research and policy-based organizations as well as consulting firms, universities, and individual academicians. Throughout the policy development process of the Patient Protection and Affordable Care Act (ACA) of 2010, estimates from several health-related MSMs received considerable attention by policy makers and interested stakeholders seeking objective estimates of the potential effectiveness and economic implications of the legislation. Notably, with the passage of the ACA, many of the major health policy simulation models continue to be used throughout implementation to assess how key provisions may affect specific populations. While potential users or contractors of microsimulation modeling are diverse, there are likely common issues faced by each when choosing a model and modeling strategy. To provide a foundation for understanding the role of microsimulation in health policy making activities, this article addresses the following three questions: Who uses health-related MSMs and for what purpose? What are the constraints and challenges faced by potential users when making decisions about models and modeling strategy? What are some areas for improvement and investment for the development and use of health-related MSMs in future policy making activities?