State and Local Coverage Changes Under Full Implementation of the Affordable Care Act
Based on the IRS tax definition of modified adjusted gross income (MAGI)—for more details on MAGI income definition, see: Buettgens, M., D. Resnick, V. Lynch, and C. Carroll. 2013. Documentation on the Urban Institute’s American Community Survey Health Insurance Policy Microsimulation Model (ACS-HIPSM.) The Urban Institute. Washington DC.
Sommers, B.D. and A.M. Epstein. 2010. “U.S. Governors and the Medicaid Expansion — No Quick Resolution in Sight.” New England Journal of Medicine 368(6): 496-499.
Holahan, J., M. Buettgens, C. Carroll, and S. Dorn. 2012. “The Cost and Coverage Implications of the ACA Medicaid Expansion: National and State-by-State Analysis.” Washington, DC: Kaiser Family Foundation.
Clemans-Cope, C., G. Kenney, M. Buettgens, C. Carroll, and F. Blavin. 2012. The Affordable Care Act’s Coverage Expansions Will Reduce Differences In Uninsurance Rates By Race And Ethnicity. Health Affairs, 31(5): 920-930; Holahan, Buettgens et al. 2012; Holahan, J. and I. Headen. 2010. “Medicaid Coverage and Spending in Health Reform: National and State-by-State Results for Adults at or Below 133% FPL.” Washington, DC: Kaiser Commission on Medicaid and the Uninsured.; Dorn, S. and M. Buettgens. 2011. “Net Effects of the Affordable Care Act on State Budgets” Washington, DC: The Urban Institute.
These national estimates are consistent with other models of Medicaid enrollment increases under the ACA: Blavin F., M. Buettgens, and J Roth. 2011. “State Progress Toward Health Reform Implementation: Slower Moving States Have Much to Gain.” Washington, DC: The Urban Institute; Holahan, Buettgens et al. 2012.
While pathways through which childless adults can gain access to Medicaid coverage have existed, they’ve been limited to special categories of individuals and in most states income-based eligibility for childless adults has been very limited or nonexistent.
Spanish-speaking households are defined as households in which all the non-elderly adults speak Spanish.
This excludes Massachusetts, which we model as experiencing no change in Medicaid enrollment as a result of the ACA.
Alaska, Colorado, Florida, Georgia, Idaho, Kansas, Montana, Nevada, North Dakota, Oregon, Texas, Utah, Virginia, Wyoming.
Total includes Massachusetts.
The results of an exploratory OLS regression model indicates a positive and statistically significant relationship (p-value less than 0.05) in a given state, between share of the population below 138 percent FPL and percent increase in Medicaid , controlling for the baseline differences in Medicaid coverage (data not shown).
When we partition the total variation in area-level Medicaid/CHIP percent increases between within and across state variation, we find that variation within states accounts for 40.4 percent of the total. The rest (59.6 percent) is attributed to across state variance.
The areas with large percentage increases in their Medicaid/CHIP population do not correspond perfectly to the areas with the largest absolute Medicaid/CHIP population increases because of variation in reliance on Medicaid at baseline.
Except in Massachusetts, which, as indicated above, we model as exhibiting no change due to reform.
Nationally, we find a linear correlation between the projected changes in Medicaid enrollment and the uninsured of -0.4593 for the nonelderly.
Ponce, N., L. Ku, W. Cunningham, and R. Brown. 2006. Language Barriers to Health Care Access Among Medicare Beneficiaries. Inquiry, 43(1): 66-76.
Holahan, Buettgens et al., 2012
Ku, L., K. Jones, P. Shin, B. Bruen, and K. Hayes. 2011. “The States' Next Challenge — Securing Primary Care for Expanded Medicaid Populations.” New England Journal of Medicine, 364: 493-495.
US Census Bureau. 2009. American Community Survey.
Lynch V, and G. Kenney. 2011. “Improving the American Community Survey for Studying Health Insurance Reform.” Proceedings of the 10th Conference on Health Survey Research Methods, April 2011, Atlanta, GA. Hyattsville, MD.: Department of Health and Human Services; Lynch V., G. Kenney, J. Haley, and D. Resnick. 2011. Improving the Validity of the Medicaid/CHIP Estimates on the American Community Survey: The Role of Logical Coverage Edits. Submitted to the U.S. Census Bureau.
National Center for Health Statistics, Division of Health Interview Statistics. 2005. 2004 National Health Interview Survey (NHIS) Public Use Data Release Survey Description. Hyattsville, MD: National Center for Health Statistics.
Lynch V, M. Boudreaux, and M. Davern. 2010. “Applying and Evaluating Logical Coverage Edits to Health Insurance Coverage in the American Community Survey.” Suitland, MD.: U.S. Census Bureau, Housing and Household Economic Statistics Division.
For a description of ACS-HIPSM, see: Buettgens, M., D. Resnick, V. Lynch, and C. Carroll. 2013. Documentation on the Urban Institute’s American Community Survey Health Insurance Policy Microsimulation Model (ACS-HIPSM.) The Urban Institute. Washington DC.
Kenney G., V. Lynch, A. Cook and, S. Phong. 2010. “Who And Where Are The Children Yet To Enroll In Medicaid And The Children’s Health Insurance Program?” Health Affairs 29(10):1920-1929.Kenney, G., M. Buettgens, J. Guyer, and M. Heberlein. 2011. “Improving Coverage For Children Under Health Reform Will Require Maintaining Current Eligibility Standards For Medicaid And CHIP.” Health Affairs, 30(12): 2371-2381; Kenney G., V. Lynch, J. Haley, M. Huntress, D. Resnick, and C. Coyer. 2011. “Gains for Children: Increased Participation in Medicaid and CHIP in 2009.” Washington, DC: The Urban Institute; Kenney G., V. Lynch, J. Haley, and M. Huntress. 2012. “Variation in Medicaid Eligibility and Participation among Adults: Implications for the Affordable Care Act.” Inquiry, 49(3): 231-253.
Family-level characteristics used in determining pre-ACA eligibility, such as income, are based on the family groupings that states define during the process of determining eligibility under pre-ACA rules. However, indicators for “family” characteristics discussed in this paper refer to the family unit that is generally eligible for the same private plan, known as the health insurance unit (HIU). Eligibility for CHIP coverage is defined according to whether the child meets the income, asset, and documentation requirements for coverage and does not take into account whether the child might be subject to a waiting period.
Cohen Ross, D., M. Jarlenski, S. Artiga, and C. Marks. 2009. “A Foundation for Health Reform: Findings of a 50 State Survey of Eligibility Rules, Enrollment and Renewal Procedures, and Cost- Sharing Practices in Medicaid and CHIP for Children and Parents During 2009.” Washington, D.C.: Kaiser Commission on Medicaid and the Uninsured; Heberlein et al., 2011, 2012; Kaiser Commission on Medicaid and the Uninsured. 2010. Expanding Medicaid to Low-Income Childless Adults under Health Reform: Key Lessons from State Experiences. Publication No. 8087. Washington, D.C.: Kaiser Commission on Medicaid and the Uninsured; Kaiser Commission on Medicaid and the Uninsured. 2011. Where are States Today? Medicaid and CHIP Eligibility Levels for Children and Non-Disabled Adults. Publication No. 7993-02. Washington, D.C.: Kaiser Commission on Medicaid and the Uninsured.
National Immigration Law Center. 2011. Table: Medical Assistance Programs for Immigrants in Various States. ; Sullivan, J. 2010. “Expanding Coverage for Recent Immigrants: CHIPRA Gives States New Options.” Washington, DC: Families USA.; Heberlein, M., T. Brooks, J. Guyer, S. Artiga, and J. Stephens. 2011. Holding Steady, Looking Ahead: Annual Findings of a 50-State Survey of Eligibility Rules, Enrollment and Renewal Procedures, and Cost-Sharing Practices in Medicaid and CHIP, 2010–2011. Washington, D.C. Kaiser Commission on Medicaid and the Uninsured; Heberlein, M., T. Brooks, J. Guyer, S. Artiga, and J. Stephens. 2012. Performing Under Pressure: Annual Findings of a 50-State Survey of Eligibility, Enrollment, Renewal, and Cost-Sharing Policies in Medicaid and CHIP, 2011–2012. Washington, D.C.: Kaiser Commission on Medicaid and the Uninsured.
Documentation status is imputed to immigrants in two stages using individual and family characteristics, based on an imputation methodology that was originally developed by Passel (Passel and Cohen, 2008). The approach is designed to produce imputations that match, in the aggregate, published summary estimates of the U.S. undocumented population, nationally and in a subset of large states.
Kenney, G., V. Lynch, A. Cook, and S. Phong. 2010b. Who And Where Are The Children Yet To Enroll In Medicaid And The Children’s Health Insurance Program? Health Affairs, 29(10): 1920-1929.
We use “tax unit” and “HIU” or “health insurance unit” interchangeably in this report.
Based on the most recent regulations as of this analysis, we assume maintenance-of-eligibility for children and for adults not above 138% FPL in an 1115 waiver or limited benefit program (federally- or state-funded programs that offer substantially more limited medical services, higher cost sharing, or other limitations).
We apply this simulation approach to all individuals except those in Massachusetts, whom we assume will experience no change in health insurance status due to ACA implementation.
States’ determinations of disability-related eligibility use additional criteria than the indicators of functional limitations available on the ACS. Thus, some of the sample people who appear in our model to be eligible through the disability pathway might not qualify when the more detailed information on their characteristics is taken into account.
Demographic Composition of Medicaid CHIP Enrollees (0-64), Pre and Post Affordable Care Act Implementation with All States Expanding Medicaid
Increase in Number (0 to 64) with Medicaid/CHIP Coverage with All States Expanding Medicaid
Increase in Medicaid/CHIP Population (0-64) Under ACA with All States Expanding Medicaid
Distribution of Percent Change of Area-level Medicaid/CHIP Coverage Under the ACA with All States Expanding Medicaid, by State
Top 50 Areas by Share of Medicaid/ CHIP Population in a Spanish Speaking Household with All States Expanding Medicaid
Reduction in Number of Uninsured (0 to 64) Under the ACA with All States Expanding Medicaid
Current Share of Nonelderly Population Who Are Uninsured
Share of Nonelderly Population Uninsured Under ACA with All States Expanding Medicaid
Share of Population (0 to 64) who would be Uninsured Under the ACA with All States Expanding Medicaid, Top 50 Areas
Demographic Composition of the Uninsured (0 to 64), Pre and Post ACA Implementation with All States Expanding Medicaid
Demographics of Medicaid/CHIP Enrollees (0 to 64) in Texas, Pre and Post ACA Implementation with the Medicaid Expansion
Increase in Medicaid/CHIP Population in Texas with ACA Medicaid Expansion
Increase in Medicaid/ CHIP Population (0-64) Across Areas in Texas Under the ACA with the Medicaid Expansion
Reduction in Uninsurance (0 to 64) Across Areas in Texas Under the ACA with the Medicaid Expansion
Demographics of Medicaid/CHIP Enrollees (0 to 64) in Illinois, Pre and Post ACA Implementation with the Medicaid Expansion
Increase in Medicaid/CHIP Population in Illinois with ACA Medicaid Expansion
Increase in Medicaid/ CHIP Population (0-64) Across Areas in Illinois Under the ACA with the Medicaid Expansion
Reduction in Uninsurance (0 to 64) Across Areas in Illinois Under the ACA with the Medicaid Expansion
Substate Areas Defined for Assessing Health Insurance Coverage on the American Community Survey
Number of Constructed Areas in Each State
also of interest
- New Animation Explains Changes Coming for Americans Under Obamacare
- Medicaid Moving Forward
- The Uninsured: A Primer
- Key Lessons from Medicaid and CHIP for Outreach and Enrollment Under the Affordable Care Act
- Faces of the Medicaid Expansion: Experiences and Profiles of Uninsured Adults Who Could Gain Coverage