Past Disruptions in Health Insurance Coverage and Access to Care Among Insured Adults

Am J Prev Med. 2023 Mar;64(3):405-413. doi: 10.1016/j.amepre.2022.10.005. Epub 2022 Dec 24.


Introduction: Although the association between health insurance coverage and access to care is well documented, it is unclear whether the deleterious effects of being uninsured are strictly contemporaneous or whether previous disruptions in coverage have persistent effects. This study addresses this issue using nationally representative data covering 2011-2019 to estimate the extent to which disruptions in health insurance coverage continued to be associated with poor access even after coverage was regained.

Methods: Analysis was conducted in 2022. Using a nationally representative cohort of insured adults aged 18-64 years (N=39,904) and multivariable logistic regression models, the authors estimated the association between past disruptions in coverage (occurring at least 1 year before) and the risks of lacking a usual source of care provider and having unmet medical need.

Results: Among insured nonelderly adults, the risk of being without a usual source of care provider was between 18% (risk ratio=1.18; 95% CI=1.00, 1.38) and 75% higher (risk ratio=1.75; 95% CI=1.56, 1.93) than for those with continuous coverage; the risk of having unmet medical needs was between 41% (risk ratio=1.41; 95% CI=1.00, 1.83) and 66% (risk ratio=1.66; 95% CI=1.26, 2.06) higher. Longer insurance disruptions were associated with a higher risk of lacking a usual source of care provider.

Conclusions: Previous disruptions in health insurance coverage continued to be negatively associated with access to care for more than a year after coverage was regained. Improving access to care in the U.S. may require investing in policies and programs that help to strengthen coverage continuity among individuals with insurance coverage rather than focusing exclusively on helping uninsured individuals to gain coverage.

MeSH terms

  • Adult
  • Health Services Accessibility*
  • Humans
  • Insurance Coverage
  • Insurance, Health*
  • Logistic Models
  • Medically Uninsured
  • United States