Advertisement

Health Insurance Disruptions and Care Access and Affordability in the U.S.

      Introduction

      Health insurance is associated with better care in the U.S., but little is known about the associations of coverage disruptions (i.e., periods without insurance) with care access, receipt, and affordability.

      Methods

      Adults aged 18–64 years with current private (n=124,746), public (n=30,932), or no (n=31,802) insurance coverage were identified from the 2011–2018 National Health Interview Survey. Data were analyzed in 2020. Separate multivariable logistic regressions evaluated the associations of having coverage disruptions or being uninsured with care access, receipt, and affordability.

      Results

      Overall, 5.0% of currently insured adults with private and 10.7% with public insurance reported a coverage disruption in the previous year, representing nearly 9.1 million adults in 2018. Among currently uninsured, 24.9% reported coverage loss within the previous year, representing nearly 8.1 million adults in 2018. Among adults with current private or current public coverage, disruptions were associated with lower receipt of all preventive services (AOR=0.42, 95% CI=0.37, 0.46 and AOR=0.48, 95% CI=0.40, 0.58, respectively), with forgoing any needed care because of cost (AOR=4.79, 95% CI=4.44, 5.17 and AOR=4.28, 95% CI=3.86, 4.75), and with medication nonadherence because of cost (AOR=3.55, 95% CI=3.13, 4.03 and AOR=4.09, 95% CI=3.43, 4.88) compared with that among adults with continuous coverage (p<0.05). Longer disruptions among currently insured adults were significantly associated with worse care access, receipt, and affordability, with dose–response patterns. Currently uninsured adults, especially those with longer uninsured periods, reported significantly worse care access, receipt, and affordability than currently insured adults with coverage disruptions or continuous coverage.

      Conclusions

      Findings highlight the importance of continuous insurance coverage; disruptions owing to the COVID-19 pandemic will likely have adverse consequences for care access and affordability.
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to American Journal of Preventive Medicine
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      REFERENCES

        • Institute of Medicine, Board on Health Care Services, Committee on Health Insurance Status and Its Consequences
        America's Uninsured Crisis: Consequences for Health and Health Care.
        The National Academies Press, Washington, DC2009https://doi.org/10.17226/12511
        • Wallace J
        • Sommers BD
        Health insurance effects on preventive care and health: a methodologic review.
        Am J Prev Med. 2016; 50: S27-S33https://doi.org/10.1016/j.amepre.2016.01.003
        • Yabroff KR
        • Zhao J
        • Han X
        • Zheng Z
        Prevalence and correlates of medical financial hardship in the USA.
        J Gen Intern Med. 2019; 34: 1494-1502https://doi.org/10.1007/s11606-019-05002-w
        • Woolhandler S
        • Himmelstein DU
        The relationship of health insurance and mortality: is lack of insurance deadly?.
        Ann Intern Med. 2017; 167: 424-431https://doi.org/10.7326/M17-1403
        • Sommers BD
        • Gunja MZ
        • Finegold K
        • Musco T
        Changes in self-reported insurance coverage, access to care, and health under the Affordable Care Act.
        JAMA. 2015; 314: 366-374https://doi.org/10.1001/jama.2015.8421
        • Sommers BD
        • Gawande AA
        • Baicker K
        Health insurance coverage and health-what the recent evidence tells us.
        N Engl J Med. 2017; 377: 586-593https://doi.org/10.1056/NEJMsb1706645
        • Sommers BD
        • Baicker K
        • Epstein AM
        Mortality and access to care among adults after state Medicaid expansions.
        N Engl J Med. 2012; 367: 1025-1034https://doi.org/10.1056/NEJMsa1202099
        • Short PF
        • Graefe DR
        • Swartz K
        • Uberoi N
        New estimates of gaps and transitions in health insurance.
        Med Care Res Rev. 2012; 69: 721-736https://doi.org/10.1177/1077558712454195
        • Villarroel MA
        • Cohen RA
        Health insurance continuity and health care access and utilization, 2014.
        NCHS Data Brief. 2016; (https://www.cdc.gov/nchs/data/databriefs/db249.pdf. Accessed March 9, 2021): 1-8
        • Ginde AA
        • Lowe RA
        • Wiler JL
        Health insurance status change and emergency department use among U.S. adults.
        Arch Intern Med. 2012; 172: 642-647https://doi.org/10.1001/archinternmed.2012.34
        • Roberts ET
        • Pollack CE
        Does churning in Medicaid affect health care use?.
        Med Care. 2016; 54: 483-489https://doi.org/10.1097/MLR.0000000000000509
        • Sommers BD
        • Gourevitch R
        • Maylone B
        • Blendon RJ
        • Epstein AM
        Insurance churning rates for low-income adults under health reform: lower than expected but still harmful for many.
        Health Aff (Millwood). 2016; 35: 1816-1824https://doi.org/10.1377/hlthaff.2016.0455
        • Yabroff KR
        • Reeder-Hayes K
        • Zhao J
        • et al.
        Health insurance coverage disruptions and cancer care and outcomes: systematic review of published research.
        J Natl Cancer Inst. 2020; 112: 671-687https://doi.org/10.1093/jnci/djaa048
        • Ji X
        • Wilk AS
        • Druss BG
        • Cummings JR
        Effect of Medicaid disenrollment on health care utilization among adults with mental health disorders.
        Med Care. 2019; 57: 574-583https://doi.org/10.1097/MLR.0000000000001153
        • Ramsey SD
        • Zeliadt SB
        • Richardson LC
        • et al.
        Disenrollment from Medicaid after recent cancer diagnosis.
        Med Care. 2008; 46: 49-57https://doi.org/10.1097/MLR.0b013e318158ec7f
        • Graubard BI
        • Korn EL
        Predictive margins with survey data.
        Biometrics. 1999; 55: 652-659https://doi.org/10.1111/j.0006-341x.1999.00652.x
        • VanderWeele TJ
        • Ding P
        Sensitivity analysis in observational research: introducing the E-value.
        Ann Intern Med. 2017; 167: 268-274https://doi.org/10.7326/M16-2607
      1. Employment situation news release: the employment situation – April 2020. U.S. Bureau of Labor Statistics. https://www.bls.gov/news.release/archives/empsit_05082020.htm. Updated September 23, 2020. Accessed March 9, 2021.

      2. Employment situation news release: the employment situation – September 2020. U.S. Bureau of Labor Statistics. https://www.bls.gov/news.release/archives/empsit_10022020.htm. Updated October 5, 2020. Accessed March 9, 2021.

        • Carfì A
        • Bernabei R
        • Landi F
        Gemelli Against COVID-19 Post-Acute Care Study Group. Persistent symptoms in patients after acute COVID-19.
        JAMA. 2020; 324: 603-605https://doi.org/10.1001/jama.2020.12603
        • Goldman AL
        • Sommers BD
        Among low-income adults enrolled in Medicaid, churning decreased after the Affordable Care Act.
        Health Aff (Millwood). 2020; 39: 85-93https://doi.org/10.1377/hlthaff.2019.00378
      3. Medicaid income eligibility limits for adults as a percent of the federal poverty level. Kaiser Family Foundation. https://www.kff.org/health-reform/state-indicator/medicaid-income-eligibility-limits-for-adults-as-a-percent-of-the-federal-poverty-level/. Updated January 1, 2021. Accessed March 9, 2021.

        • Cohen RA
        • Zammitti EP
        High-deductible health plan enrollment among adults aged 18-64 with employment-based insurance coverage.
        NCHS Data Brief. 2018; (https://www.cdc.gov/nchs/products/databriefs/db317.htm. Accessed March 9, 2021): 1-8