Leveraging Multiple Datasets to Evaluate the Effects of Public Health Insurance
Friday, November 3, 2017: 10:15 AM-11:45 AM
Toronto (Hyatt Regency Chicago)
*Names in bold indicate Presenter
Panel Organizers: Marguerite Burns, University of Wisconsin - Madison
Panel Chairs: Tony LoSasso, University of Illinois, Chicago
Discussants: Jim Marton, Georgia State University and Ruth Winecoff, Indiana University
Policy-makers sharply disagree about the value of investing in public health insurance programs for low-income populations as evidenced by the debate on the future of The Affordable Care Act (ACA). While the level of public expenditures for the Medicaid and Children’s Health Insurance Programs (CHIP) is well documented, estimating the value of these programs for beneficiaries and taxpayers requires quantifying both their direct and spillover effects. The research presented in this panel provides evidence to support such an assessment. Notably, and in keeping with the conference theme, each of the panel’s four papers generates this evidence through the innovative use of multiple datasets including public, restricted, and primary data sources. The first paper exploits the ACA-related Medicaid coverage expansion in West Virginia to characterize opioid addiction diagnosis rates, treatment use patterns, and adverse outcomes among the newly insured. The author further investigates the influence of provider supply and rurality on these outcomes by combining the state’s Medicaid claims data with county-level health and health care market data. The panel’s second paper evaluates if and how the introduction of Medicaid coverage for adults without dependent children improves their mental health outcomes. The study’s dataset combines 12 panels of the restricted Medical Expenditure Panel Survey from 2001-2013 to data that the authors collected characterizing Medicaid coverage for childless adults in all states and study years. The panel’s third paper evaluates how the initial creation and continued expansions of CHIP in the late 1990s and early 2000s affected Supplemental Security Income applications and awards among exposed cohorts. The authors’ key data sources for the study are the Current Population Survey and the Social Security Administration’s Supplemental Security Record. The fourth and final paper estimates the effect of ACA-related Medicaid expansions on participation in the Supplemental Nutrition Assistance Program (SNAP) among low-income parents and adults without dependent children. The authors implement their main analyses using the American Community Survey and conduct robustness analyses with an alternative source of data, SNAP administrative data.