VII. Key Issues: Regulation & Reform >> Health Reform >> Modeling the Impact of Health Reform (last updated 4.9.17)
Congressional Budget Office
The Congressional Budget Office is principally responsible for scoring legislative proposals before Congress. It provides an “official” (and rarely contested) score of the impact of various legislative proposals on coverage, costs and the federal budget.
- Detailed Description (October 2007). CBO’s Health Insurance Simulation Model: A Technical Description (October 2007). Over the past several years, federal and state policymakers have considered a variety of proposals to increase health insurance coverage among the nation’s residents. Estimating the effects of those proposals on the size of the uninsured population, the cost of health insurance premiums, and the federal budget is a significant challenge. This background paper describes a model the Congressional Budget Office (CBO) developed to simulate and analyze an array of policy options involving health insurance coverage. It describes the model’s design, basic methodology, and fundamental assumptions. To illustrate the model’s use, the paper reports estimates for two scenarios in which policy regarding health insurance coverage would differ from current law.
- PowerPoint Overview (11.3.15). Microsimulation of Demand for Health Insurance. CBO’s health insurance simulation model (HISIM) is an important tool for estimating the budgetary and coverage effects of the insurance coverage provisions of the Affordable Care Act. HISIM relies on data from the Medical Expenditure Panel Survey (MEPS) in two critical areas. The model uses individual level spending data from the MEPS Household Component to estimate individual health risk and benchmarks employer premiums to the MEPS Insurance Component data.
Center for Health and Economy
The Center for Health and Economy is a think tank led by Douglas Holtz-Eakin, a former director of the Congressional Budget Office. Its board includes leading health economists such as Mark Pauly (Wharton School, University of Pennsylvania), Uwe Reinhardt (Princeton), Stephen Parente (Carlson School of Business, University of Minnesota), and Michael Morrissey (University of Alabama). H&E has developed a microsimulation model that differs from the one used by CBO. But too many proposals cannot get scored by the CBO. A House or Senate member who doesn’t sit on one of the key fiscal committees in Congress cannot have a plan scored unless it is co-sponsored by someone else on one of those key committees. Similarly, a plan developed by someone at a think-tank or a university cannot get CBO to score their proposal. H&E is intended to fill this major policy void, by providing an alternative route to getting health reforms fiscally scored. As well, it can both hold CBO accountable and even improve the quality of CBO’s own analysis by providing an outside alternative to CBO’s estimates of the fiscal impact of bills before Congress.
Gruber Microsimulation Model (GMSIM)
GMSIM was developed by Jonathan Gruber, a health economist at MIT who was heavily involved in the development of the Massachusetts health reform plan (“Romneycare”) and the Affordable Care Act.
- Powerpoint Overview. The Gruber MicroSimulation Model (GMSIM) (February 2009).
- Narrative Overview. Short Description of Gruber Microsimulation Model.
- Detailed Description.
- Published Model Results.
- Senate High Cost Insurance Tax Will Raise Wages
- Gruber Senate Premium Analysis 11-27-09
- National Affordability Report
- FamiliesUSA Methodology. The Bottom Line: How the Affordable Care Act Helps America’s Families.
- Massachusetts Affordability Report
- Report on Schwarzenegger Administration Health Proposal
- Health Care Reform (“Graphic Novel”). Written by Gruber to explain the Affordable Care Act to the general public.
- Health Care Reform: What It Is, Why It’s Necessary, How It Works. (Hill and Wang, December 20, 2011) “You won’t have to worry about going broke if you get sick. We will start to bring the costs of health care under control. And we will do all this while reducing the federal deficit. That is the promise of the Affordable Care Act.”
- Everything You Wanted to Know about Health Reform, in One Comic Book. “Do you like comic books with CBO scores, two-headed alligators and health economist superheroes? Then has Jonathan Gruber got a graphic novel for you!… The Congressional Budget Office makes multiple appearances.” Kliff, Sarah. (Washington Post, 10.11.11)
- Sins of Omission: What’s Wrong With Gruber’s Health Care Reform. “[I]n all honesty, the book is awful. Gruber crafts his argument like a salesman, not an economic educator. He’s careful to avoid outright mistakes, and makes a couple of awkward disclosures. Yet he omits a long list of crucial, damaging points… Gruber emphasizes how ‘complicated’ cost control is. But we should support Obamacare anyway.” Caplan, Brian, Library of Economics and Liberty. (EconLog. EconLib.org, 1.4.12)
- Eight Goofs in Jonathan Gruber’s Health Care Reform Book. Palumbo, Matt. (Foundation for Economic Education, 2.17.15)
- Outcomes in Massachusetts.
- Arguable: With Successes Like that, Who Needs Failure? “It has been 11 years since former Governor Mitt Romney signed into law the health-care overhaul that later became the model for the ACA. The chief architect of Romneycare was MIT’s Jonathan Gruber, who later played a key role in drafting Obamacare and famously said that there was zero difference between the two laws. (In Gruber’s elegant formulation: ‘It’s the same f—ing bill.’)… Behold the Massachusetts health-care triumph: Government set out to control the health-care and health insurance markets through an ever-more-intricate web of mandates, subsidies, regulations, and price controls, and achieved near-universal health coverage. What that means in practice is that patients in Massachusetts not only pay a lot more money for insurance and medical care than they used to, but they also wait far longer to see a new doctor than they used to.” (Boston Globe, 3.28.17)
Health Benefits Simulation Model (HBSM)
This model developed at Lewin Group–a 40 year old health care and human services consulting firm–is one of the oldest, having been first developed to analyze the impact of health reform proposals during the late 1980’s. The Lewin Group currently is an Optum company, a wholly owned subsidiary of UnitedHealth Group.
- Detailed Description. Health Benefits Simulation Model (HBSM) Summary Documentation (September 2010). The Health Benefits Simulation Model (HBSM) is a micro-simulation model of the US health care system. HBSM is a fully integrated platform for simulating policies ranging from narrowly defined insurance market regulations to Medicaid coverage expansions and broad-based reforms involving multiple programs. The model has been adapted to simulate the impact of the Affordable Care Act (ACA) and can be used to model other health reform proposals.
- Published Model Results.
- Society of Actuaries. Cost of the Future Newly Insured under the Affordable Care Act (ACA) (March 2013). This study used the HBSM to estimate the impact of the ACA on medical costs (per member per month) and coverage, by state. The report extensively documents the sources and methods used to generate the results.
- Lewin Group. John Sheils and Randall Haught. Modeling Health Reform without the Mandate to Have Coverage (9.29.11). Staff Working Paper #14. In this paper, we present our estimates of the coverage effects of the ACA with and without a mandate for all to have coverage. We did this by incorporating “utility” functions that permit us to explicitly model the impact of perceived risk and risk aversion on the decision to take coverage. We used this approach to model changes in take-up when regulations change the risk consequences of being uninsured, such as open enrollment periods and pre-existing condition exclusions.
The Health Economic Policy Simulation System (HEPPS)–formerly Adjusted Risk Choice & Outcomes Legislative Assessment (ARCOLA)–model is a microsimulation model developed over more than a decade by Stephen T. Parente, a health economist at University of Minnesota’s Carlson School of Business. While CBO, GMSIM, RAND and Urban Institute models all share similar structures built around similar large public datasets such as the Medical Expenditure Survey, the HEPPS model is unique on having been built from proprietary claims data that offer a much more fine-grained assessment of plan choices that face consumers under various health reform plans, including the Affordable Care Act. Analysis using this model that are in the public domain include:
- Parente, S. T., & Feldman, R. (2013). Microsimulation of Private Health Insurance and Medicaid Take-Up Following the U.S. Supreme Court Decision Upholding the Affordable Care Act. Health Services Research, 48(2pt2), 826-849. doi: 10.1111/1475-6773.12036. Abstract. Full Text pdf.
- Parente, Stephen T. and Tarren Bragdon. Healthier Choice: An Examination of Market-Based Reforms for New York’s Uninsured. Medical Progress Report No. 10, September 2009. This report uses the ARCOLA model and explains in detail the model’s workings.
- Parente, Stephen T. et al. Consumer Response to a National Marketplace for Individual Insurance (June 28, 2008).
RAND Health researchers developed the COMPARE microsimulation model as a way of projecting how households and firms would respond to health care policy changes based on economic theory and existing evidence from smaller-scale changes (e.g., changes in Medicaid eligibility).
- Narrative Overview. How the RAND COMPARE Microsimulation Model Works.
- Detailed Description. The 9-page Appendix to Effects of the Affordable Care Act on Consumer Health Care Spending and Risk of Catastrophic Health Costs (September 2013) includes a description of the updated RAND COMPARE model. Earlier details about how the model works are located in Appendix A of a report on establishing state health insurance exchanges and Appendix D of a report on employer self-insurance decisions after the ACA takes full effect.
- Published Model Results.
- Nowak, Sarah A., Christine Eibner, David M. Adamson and Evan Saltzman. Effects of the Affordable Care Act on Consumer Health Care Spending and Risk of Catastrophic Health Costs. Santa Monica, CA: RAND Corporation, September 2013. This study examines the likely effects of the Affordable Care Act (ACA) on average annual consumer health care spending and the risk of catastrophic medical costs for the United States overall and in two large states that have decided not to expand their Medicaid programs (Texas and Florida).
- Eibner, Christine, Amado Cordova, Sarah A. Nowak, Carter C. Price, Evan Saltzman and Dulani Woods. The Affordable Care Act and Health Insurance Markets: Simulating the Effects of Regulation. Santa Monica, CA: RAND Corporation, August 2013. In this report, the authors estimate the effects of the Affordable Care Act on health insurance enrollment and premiums for ten states (Florida, Kansas, Louisiana, Minnesota, New Mexico, North Dakota, Ohio, Pennsylvania, South Carolina, and Texas) and for the nation overall, with a focus on outcomes in the nongroup and small group markets.
- Cordova, Amado, Federico Girosi, Sarah A. Nowak, Christine Eibner, Kenneth Finegold. The COMPARE Microsimulation Model and the U.S. Affordable Care Act. International Journal of Microsimulation, v. 6, no. 3, Winter 2013, p. 78-117. In this paper we provide a summary of COMPARE’s basic principles, its nationally representative databases, its utility-maximization behavioral models, and how we have used COMPARE to estimate the consequences of the Affordable Care Act.
- State Level Analyses. The model has been used to estimate the impacts of ACA in CA, CT, IL, MT, and TX.
The Urban Institute model was originally developed using the Transfer Income Model, version 3 (TRIM3), a comprehensive micro-simulation model developed and maintained at the Urban Institute under primary funding from the U.S. Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation (HHS/ASPE). TRIM3 simulates the major governmental tax, transfer, and health programs that affect the U.S. population, and it can produce results at the individual, family, state, and national levels. It is a cell-based model but (like ARCOLA) is capable of making individual predictions. Since the first TRIM model became operational in 1973, TRIM models have been used to generate potential outcomes of public-policy changes in the areas of welfare reform, tax reform, national health-care reform, and so forth.
- Detailed Description.
- Health Insurance Policy Simulation Model Methodology Documentation, 2011 National Version (December 14, 2011). The Health Insurance Policy Simulation Model (HIPSM) is a detailed microsimulation model of the health care system. It estimates the cost and coverage effects of proposed health care policy options. HIPSM is designed for quick‐turnaround analysis of policy proposals. It can be rapidly adapted to analyze a wide variety of new scenarios—from novel health insurance offerings and strategies for increasing affordability to state‐specific proposals—and can describe the effects of a policy option at a number of points in time (pdf).
The Urban Institute’s Health Microsimulation Capabilities. This report summarizes HIPSM’s capabilities and a
list of recent research using it.
- Published Model Results.
- Urban Institute, on behalf of the New York State Department of Health and Insurance 2009. Achieving Quality, Affordable Health Insurance for All New Yorkers: An Analysis of Reform Options.
- Abraham, Jean M. State Health Reform Assistance Network, Predicting the Effects of the Affordable Care Act: A Comparative Analysis of Policy Microsimulation Models (March. 2012).
- Glied S and Tilipman N. 2010. Simulation Modeling of Health Care Policy. Annual Review of Public Health. 31: 439-55.
- Parente, Stephen T. and Tarren Bragdon. Healthier Choice: An Examination of Market-Based Reforms for New York’s Uninsured. Medical Progress Report No. 10, September 2009. This report does a side-by-side comparison of results from the ARCOLA model, Columbia University model and Urban Institute model (2009) and explains in detail the models’ workings.