Medicaid Expansion and Medical Debt: Evidence From Louisiana, 2014–2019

Objectives. To identify the association between Medicaid eligibility expansion and medical debt. Methods. We used difference-in-differences design to compare changes in medical debt for those gaining coverage through Louisiana’s Medicaid expansion with those in nonexpansion states. We matched individuals gaining Medicaid coverage because of Louisiana’s Medicaid expansion (n=196 556) to credit report data on medical debt and compared them with randomly selected credit reports of those living in Southern nonexpansion state zip codes with high rates of uninsurance (n=973 674). The study spanned July 2014 through July 2019. Results. One year after Louisiana Medicaid expansion, medical collections briefly rose before declining by 8.1 percentage points (95% confidence interval [CI]=–0.107, –0.055; P≤.001), or 13.5%, by the third postexpansion year. Balances also briefly rose before falling by 0.621 log points (95% CI=–0.817, –0.426; P≤.001), or 46.3%. Conclusions. Louisiana’s Medicaid expansion was associated with a reduction in the medical debt load for those gaining coverage. These results suggest that future Medicaid eligibility expansions may be associated with similar improvements in the financial well-being of enrollees. (Am J Public Health. Published online ahead of print July 2, 2021: e1–e7. https://doi.org/10.2105/AJPH.2021.306316 )

The Financial Burden of Cancer on Families in the United States

This study examined the relationship between a diagnosis of cancer and the likelihood of having any out-of-pocket costs (OOPC) and medical debt, and the amounts of OOPC and medical debt, at the household level. We used the 2013 Panel Study of Income Dynamics, a continuous, representative panel survey that collects demographic, economic, and social data in the United States. The analytic sample included head of households and their spouse (if married), 18–64 years old. Two-part models were used. The first part consisted of logistic regression models and the second part consisted of generalized linear models with logarithmic link and a gamma distribution. Logistic regression results showed odds of 2.13 (CI: 1.27, 3.57, p < 0.01) for any OOPC and odds of 1.55 (CI: 0.93, 2.58, p < 0.1) for any medical debt for households in which either the head or spouse (if married) reported a diagnosis of cancer compared to those that did not report a diagnosis of cancer. Likewise, results from the second part of the model for households with a positive amount of OOPC showed an exponentiated coefficient of 1.73 (CI: 1.33, 2.25, p < 0.01) for households in which either the head or spouse (if married) reported a diagnosis of cancer compared to households without a diagnosis of cancer. This study shows that a diagnosis of cancer places a financial burden on families, particularly with all types of debt, in the United States even after controlling for differences between households with a diagnosis of cancer and those without a diagnosis of cancer.

Contact by Collection Agencies for Medical Debt: Rural–Urban Differences Among Older and Younger Medicare Beneficiaries

Geographic disparities in health and health care are increasingly well-documented, as are financial barriers to accessing care. Still, less is known about whether Medicare beneficiaries differ in their ability to pay for care by rurality. Using data from the 2016 Medicare Current Beneficiary Survey ( n = 12,688 U.S. community-dwelling beneficiaries), we analyzed rural–urban differences in rates of collection agency contact for unpaid medical bills using chi-square tests and multivariable logistic regression for the full sample and by age (65+ and <65). Nearly 10% of Medicare beneficiaries had been contacted by a collection agency for medical debt in the previous year, with higher percentages among rural beneficiaries (8% for urban vs 10% for rural micropolitan and 11% for rural noncore, p < .05). This difference attenuated after adjusting for educational attainment and income, suggesting that attention to socio-economic status among rural Medicare beneficiaries would help to address financial barriers to care and decrease medical debt.