COMPARE is a microsimulation model that predicts the effects of health policy changes at national and state levels. The model takes a synthetic data set with information on a nationally representative sample of individuals and their employers and predicts how they will react under different policy scenarios. Our model has been used extensively in the wake of the 2010 Patient Protection and Affordable Care Act (ACA) to estimate the effects of health reform on key outcomes, including the number of people with health coverage, the number of people who will buy coverage through the new insurance exchanges, the number of firms that will offer coverage, and government spending. This page is intended to provide information to policymakers, researchers, and other individuals who are interested in contacting the COMPARE team or using the model to estimate the effects of policy changes.
Read More About How the Microsimulation Model Works
The Affordable Care Act (ACA) will increase coverage through the expansion of Medicaid and the creation of a Health Insurance Exchange with subsidies. RAND researchers analyzed the ACA’s economic impact on the state of Arkansas.
Implications of the Patient Protection and Affordable Care Act of 2010 (as Modified by the Health Care and Education Reconciliation Act) for small firms' decisions to offer self-insured health plans and consequences of self-insurance for enrollees.
Projects how the coverage-related provisions of the Patient Protection and Affordable Care Act will affect health insurance coverage and state government spending on health care in five states.
For California, the model predicts that, in 2016 (the year that all of the provisions in the ACA related to coverage expansion will be fully implemented), the uninsured rate in California will fall to 4 percent; without the law, it would remain at 20 percent. The model projects that total state government spending on health care will be 7 percent higher for the combined 2011–2020 period because of the ACA.
For Connecticut, the model predicts that, in 2016 (the year that all of the provisions in the ACA related to coverage expansion will be fully implemented), the uninsured rate in Connecticut will fall to 5 percent; without the law, it would remain at 11 percent. The model projects that total state government spending on health care will be 10 percent lower for the combined 2011–2020 period than it would be without the ACA, mostly because of federal subsidies for residents who would have been covered by Connecticut's state-run health insurance program (State-Administered General Assistance).
For Illinois, the model predicts that, in 2016 (the year that all of the provisions in the ACA related to coverage expansion will be fully implemented), the uninsured rate in Illinois will fall to 3 percent; without the law, it would remain near 15 percent. The model projects that total state government spending on health care will be 10 percent higher for the combined 2011–2020 period because of the ACA.
For Montana, the model predicts that, in 2016 (the year that all of the provisions in the ACA related to coverage expansion will be fully implemented), the uninsured rate in Montana will fall to 3 percent; without the law, it would remain at 18 percent. The model projects that total state government spending on health care will be 3 percent higher for the combined 2011–2020 period because of the ACA.
For Texas, the model predicts that, in 2016 (the year that all of the provisions in the ACA related to coverage expansion will be fully implemented), the uninsured rate in Texas will fall to 6 percent; without the law, it would remain at 28 percent, the highest in the nation. The model projects that total state government spending on health care will be 10 percent higher for the combined 2011–2020 period because of the ACA.
