- is companion of
- article-commentary21 June 2016
Injecting Facts Into the Heated Debates Over Medicaid Expansion
Background:
In 2014, only 26 states and the District of Columbia chose to implement the Patient Protection and Affordable Care Act (ACA) Medicaid expansions for low-income adults.
Objective:
To evaluate whether the state Medicaid expansions were associated with changes in insurance coverage, access to and utilization of health care, and self-reported health.
Design:
Comparison of outcomes before and after the expansions in states that did and did not expand Medicaid.
Setting:
United States.
Participants:
Citizens aged 19 to 64 years with family incomes below 138% of the federal poverty level in the 2010 to 2014 National Health Interview Surveys.
Measurements:
Health insurance coverage (private, Medicaid, or none); improvements in coverage over the previous year; visits to physicians in general practice and specialists; hospitalizations and emergency department visits; skipped or delayed medical care; usual source of care; diagnoses of diabetes, high cholesterol, and hypertension; self-reported health; and depression.
Results:
In the second half of 2014, adults in expansion states experienced increased health insurance (7.4 percentage points [95% CI, 3.4 to 11.3 percentage points]) and Medicaid (10.5 percentage points [CI, 6.5 to 14.5 percentage points]) coverage and better coverage than 1 year before (7.1 percentage points [CI, 2.7 to 11.5 percentage points]) compared with adults in nonexpansion states. Medicaid expansions were associated with increased visits to physicians in general practice (6.6 percentage points [CI, 1.3 to 12.0 percentage points]), overnight hospital stays (2.4 percentage points [CI, 0.7 to 4.2 percentage points]), and rates of diagnosis of diabetes (5.2 percentage points [CI, 2.4 to 8.1 percentage points]) and high cholesterol (5.7 percentage points [CI, 2.0 to 9.4 percentage points]). Changes in other outcomes were not statistically significant.
Limitation:
Observational study may be susceptible to unmeasured confounders; reliance on self-reported data; limited post-ACA time frame provided information on short-term changes only.
Conclusion:
The ACA Medicaid expansions were associated with higher rates of insurance coverage, improved quality of coverage, increased utilization of some types of health care, and higher rates of diagnosis of chronic health conditions for low-income adults.
Primary Funding Source:
None.
References
- 1.
Dorn S ,McGrath M , andHolahan J . What Is the Result of States Not Expanding Medicaid? Washington, DC Urban Institute 2014. Google Scholar - 2. The Henry J. Kaiser Family Foundation. Current Status of State Medicaid Expansion Decisions [updated 14 March 2016]. Menlo Park, CA: The Henry J. Kaiser Family Foundation. Accessed at http://kff.org/health-reform/slide/current-status-of-the-medicaid-expansion-decision on 23 March 2016. Google Scholar
- 3. Black LI, Cohen RA. Insurance Status by State Medicaid Expansion Status: Early Release of Estimates From the National Health Interview Survey, 2013–September 2014. Hyattsville, MD: National Center for Health Statistics; 2015. Accessed at www.cdc.gov/nchs/nhis/releases.htm on 15 September 2015. Google Scholar
- 4.
Long SK ,Karpman M ,Kenney GM ,Zuckerman S ,Wissoker D ,Shartzer A , andet al . Taking Stock: Gains in Health Insurance Coverage under the ACA as of March 2015. Policy Brief. Washington, DC Urban Institute 2015. Google Scholar - 5.
Gunja M . Health Insurance Coverage and the Affordable Care Act. Issue Brief. Washington, DC Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services 2015. Google Scholar - 6.
Sommers BD ,Gunja MZ ,Finegold K , andMusco T . Changes in self-reported insurance coverage, access to care, and health under the Affordable Care Act. JAMA. 2015;314:366-74. [PMID:26219054 ] doi:10.1001/jama.2015.8421 CrossrefMedlineGoogle Scholar - 7.
Sommers BD ,Baicker K , andEpstein AM . Mortality and access to care among adults after state Medicaid expansions. N Engl J Med. 2012;367:1025-34. [PMID:22830435 ] doi:10.1056/NEJMsa1202099 CrossrefMedlineGoogle Scholar - 8.
Finkelstein A ,Taubman S ,Wright B ,Bernstein M ,Gruber J ,Newhouse JP ,et al .Oregon Health Study Group . The Oregon Health Insurance Experiment: evidence from the first year. Q J Econ. 2012;127:1057-1106. [PMID:23293397 ] CrossrefMedlineGoogle Scholar - 9.
Taubman SL ,Allen HL ,Wright BJ ,Baicker K , andFinkelstein AN . Medicaid increases emergency-department use: evidence from Oregon's Health Insurance Experiment. Science. 2014;343:263-8. [PMID:24385603 ] doi:10.1126/science.1246183 CrossrefMedlineGoogle Scholar - 10.
Baicker K ,Taubman SL ,Allen HL ,Bernstein M ,Gruber JH ,Newhouse JP ,et al .Oregon Health Study Group . The Oregon experiment—effects of Medicaid on clinical outcomes. N Engl J Med. 2013;368:1713-22. [PMID:23635051 ] doi:10.1056/NEJMsa1212321 CrossrefMedlineGoogle Scholar - 11.
National Center for Health Statistics . Survey Description. 2014 National Health Interview Survey (NHIS) Public Use Data Release. Hyattsville, MD National Center for Health Statistics 2015. Google Scholar - 12. National Center for Health Statistics. Multiple Imputation of Family Income and Personal Earnings in the National Health Interview Survey: Methods and Examples. Hyattsville, MD: National Center for Health Statistics; 2015. Accessed at www.cdc.gov/nchs/data/nhis/tecdoc14.pdf on 15 September 2015. Google Scholar
- 13. Center for Medicaid and CHIP Services. Eligibility for Non-citizens in Medicaid and CHIP. Baltimore: Centers for Medicare & Medicaid Services; 2014. Accessed at www.medicaid.gov/medicaid-chip-program-information/by-topics/outreach-and-enrollment/downloads/overview-of-eligibility-for-non-citizens-in-medicaid-and-chip.pdf on 15 September 2015. Google Scholar
- 14.
Bertrand M ,Duflo E , andMullainathan S . How much should we trust differences-in-differences estimates? Q J Econ. 2004;119:249-75. doi:10.1162/003355304772839588 CrossrefGoogle Scholar - 15.
Cameron AC andTrivedi PK . Microeconometrics: Methods and Applications. New York Cambridge Univ Pr 2007. Google Scholar - 16.
Long JS . Regression Models for Categorical and Limited Dependent Variables. Thousand Oaks, CA Sage 1997. Google Scholar - 17. National Center for Health Statistics. Variance Estimation Guidance, NHIS 2006–2014. Hyattsville, MD: National Center for Health Statistics; 2015. Accessed at www.cdc.gov/nchs/data/nhis/2006var.pdf on 15 September 2015. Google Scholar
- 18.
Cameron AC ,Gelbach JB , andMiller DL . Bootstrap-based improvements for inference with clustered errors. Rev Econ Stat. 2008;90:414-27. CrossrefGoogle Scholar - 19. Smith JC, Medalia C. Health Insurance Coverage in the United States: 2014. Current Population Reports. Washington, DC: U.S. Census Bureau; 2015. Accessed at www.census.gov/content/dam/Census/library/publications/2015/demo/p60-253.pdf on 30 November 2015. Google Scholar
- 20. Centers for Medicare & Medicaid Services. Medicaid & CHIP: October 2014 Monthly Applications, Eligibility Determinations and Enrollment Report. Baltimore: Centers for Medicare & Medicaid Services; 2014. Accessed at www.medicaid.gov/medicaid-chip-program-information/program-information/downloads/october-2014-enrollment-report.pdf on 30 November 2015. Google Scholar
- 21.
Kaufman HW ,Chen Z ,Fonseca VA , andMcPhaul MJ . Surge in newly identified diabetes among Medicaid patients in 2014 within Medicaid expansion states under the Affordable Care Act. Diabetes Care. 2015;38:833-7. [PMID:25802324 ] doi:10.2337/dc14-2334 CrossrefMedlineGoogle Scholar - 22.
Hogan DR ,Danaei G ,Ezzati M ,Clarke PM ,Jha AK , andSalomon JA . Estimating the potential impact of insurance expansion on undiagnosed and uncontrolled chronic conditions. Health Aff (Millwood). 2015;34:1554-62. [PMID:26355058 ] doi:10.1377/hlthaff.2014.1435 CrossrefMedlineGoogle Scholar - 23.
Korhonen PE ,Kivelä SL ,Kautiainen H ,Järvenpää S , andKantola I . Health-related quality of life and awareness of hypertension. J Hypertens. 2011;29:2070-4. [PMID:21946696 ] doi:10.1097/HJH.0b013e32834bbca7 CrossrefMedlineGoogle Scholar - 24.
Venkataraman K ,Khoo C ,Wee HL ,Tan CS ,Ma S ,Heng D ,et al . Associations between disease awareness and health-related quality of life in a multi-ethnic Asian population. PLoS One. 2014;9:e113802. [PMID:25426951 ] doi:10.1371/journal.pone.0113802 CrossrefMedlineGoogle Scholar - 25.
Heberlein M ,Brooks T ,Guyer J ,Artiga S , andStephens J . 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, DC The Kaiser Commission on Medicaid and the Uninsured, The Henry J. Kaiser Family Foundation; 2011. Google Scholar - 26.
Heberlein M ,Brooks T ,Guyer J ,Artiga S , andStephens J . 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, DC The Kaiser Commission on Medicaid and the Uninsured, The Henry J. Kaiser Family Foundation 2012. Google Scholar - 27.
Heberlein M ,Brooks T ,Artiga S , andStephens J . Getting into Gear for 2014: Shifting New Medicaid Eligibility and Enrollment Policies Into Drive. Washington, DC The Kaiser Commission on Medicaid and the Uninsured, The Henry J. Kaiser Family Foundation 2013. Google Scholar - 28.
Heberlein M ,Brooks T ,Alker J ,Artiga S , andStephens J . Getting into Gear for 2014: Findings from a 50-State Survey of Eligibility, Enrollment, Renewal and Cost-Sharing Policies in Medicaid and CHIP, 2012–2013. Washington, DC The Kaiser Commission on Medicaid and the Uninsured, The Henry J. Kaiser Family Foundation 2013. Google Scholar - 29.
Karaca-Mandic P ,Norton EC , andDowd B . Interaction terms in nonlinear models. Health Serv Res. 2012;47:255-74. [PMID:22091735 ] doi:10.1111/j.1475-6773.2011.01314.x CrossrefMedlineGoogle Scholar - 30.
Neyman J andScott EL . Consistent estimates based on partially consistent observations. Econometrica. 1948;16:1-32. doi:10.2307/1914288 CrossrefGoogle Scholar - 31.
Greene W . The behaviour of the maximum likelihood estimator of limited dependent variable models in the presence of fixed effects. Econom J. 2004;7:98-119. CrossrefGoogle Scholar - 32.
Wooldridge JM . Introductory Econometrics: A Modern Approach. 4th ed. Mason, OH South-Western Cengage Learning 2009. Google Scholar - 33. Dague L, DeLeire T, Leininger L. The Effect of Public Insurance Coverage for Childless Adults on Labor Supply. NBER Working Paper No. 20111. Cambridge, MA: National Bureau of Economic Research; 2014. Accessed at www.nber.org/papers/w20111 on 15 September 2015. Google Scholar
- 34.
Garthwaite C ,Gross T , andNotowidigdo M . Public health insurance, labor supply, and employment lock. Q J Econ. 2014;129:653-96. CrossrefGoogle Scholar - 35.
Angrist JD andPischke J . Mostly Harmless Econometrics: An Empiricist's Companion. Princeton Princeton Univ Pr 2009. Google Scholar - 36. The Henry J. Kaiser Family Foundation. Explaining Health Care Reform: Questions About Health Insurance Subsidies. Menlo Park, CA: The Henry J. Kaiser Family Foundation; 2014. Accessed at http://kff.org/health-reform/issue-brief/explaining-health-care-reform-questions-about-health on 15 September 2015. Google Scholar
- 37. Goldman TR. Progress Report: The Affordable Care Act's Extended Dependent Coverage Provision. Health Affairs Blog. 16 December 2013. Accessed at http://healthaffairs.org/blog/2013/12/16/progress-report-the-affordable-care-acts-extended-dependent-coverage-provision on 15 September 2015. Google Scholar
- 38. Oster E. Unobservable Selection and Coefficient Stability: Theory and Validation. NBER Working Paper No. 19 054. Cambridge, MA: National Bureau of Economic Research; 2013. Accessed at www.nber.org/papers/w19054 on 10 December 2015. Google Scholar
- 39. Oster E. PSACALC: Stata Module to Calculate Treatment Effects or Bounds Under Proportional Selection of Observables and Unobservables. 2013. Accessed at https://ideas.repec.org/c/boc/bocode/s457677.html on 10 December 2015. Google Scholar
Author, Article and Disclosure Information
Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily reflect the views of the Research Data Center, the National Center for Health Statistics, or the Centers for Disease Control and Prevention.
Acknowledgment: The authors thank Patricia Barnes and John Sullivan for their assistance in accessing the restricted-use data used in this project.
Disclosures: Authors have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M15-2234.
Editors' Disclosures: Christine Laine, MD, MPH, Editor in Chief, reports that she has no financial relationships or interests to disclose. Darren B. Taichman, MD, PhD, Executive Deputy Editor, reports that he has no financial relationships or interests to disclose. Cynthia D. Mulrow, MD, MSc, Senior Deputy Editor, reports that she has no relationships or interests to disclose. Deborah Cotton, MD, MPH, Deputy Editor, reports that she has no financial relationships or interest to disclose. Jaya K. Rao, MD, MHS, Deputy Editor, reports that she has stock holdings/options in Eli Lilly and Pfizer. Sankey V. Williams, MD, Deputy Editor, reports that he has no financial relationships or interests to disclose. Catharine B. Stack, PhD, MS, Deputy Editor for Statistics, reports that she has stock holdings in Pfizer and Johnson & Johnson.
Reproducible Research Statement:Study protocol: Not available. Statistical code: Available from Dr. Wherry (e-mail, [email protected]). Data set: Available from the National Center for Health Statistics (www.cdc.gov/rdc/index.htm).
Corresponding Author: Laura R. Wherry, PhD, Division of General Internal Medicine & Health Services Research, David Geffen School of Medicine at UCLA, 911 Broxton Avenue, Room 226, Los Angeles, CA 90024; e-mail, [email protected].
Current Author Addresses: Dr. Wherry: Division of General Internal Medicine & Health Services Research, David Geffen School of Medicine at UCLA, 911 Broxton Avenue, Room 226, Los Angeles, CA 90024.
Dr. Miller: University of Michigan, Stephen M. Ross School of Business R4416, Business Economics and Public Policy, 701 Tappan Avenue, Ann Arbor, MI 48109.
Author Contributions: Conception and design: L.R. Wherry, S. Miller.
Analysis and interpretation of the data: L.R. Wherry, S. Miller.
Drafting of the article: L.R. Wherry, S. Miller.
Critical revision of the article for important intellectual content: L.R. Wherry, S. Miller.
Final approval of the article: L.R. Wherry, S. Miller.
Statistical expertise: L.R. Wherry, S. Miller.
Administrative, technical, or logistic support: S. Miller.
Collection and assembly of data: L.R. Wherry, S. Miller.
This article was published at www.annals.org on 19 April 2016.
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