TOPLINE

Patients with cancer living in US counties with the highest levels of medical debt had an increased risk for advanced-stage diagnosis and poorer 5-year survival compared with those in counties with the lowest debt burden, according to an American Cancer Society study.

METHODOLOGY

• More than half of US cancer survivors report cancer-related medical debt, usually exceeding $5000. County-level medical debt may reflect local healthcare resources (such as charity care and financial navigation programs), hospital and physician practices related to unpaid medical bills (such as limits on care provision), and policies such as Medicaid expansion and debt forgiveness. 
• To study the association between county medical debt and cancer outcomes, researchers used the National Cancer Database (NCDB) to identify over 7.5 million US adults newly diagnosed with cancer between 2011 and 2019. 
• County-level share of adults with medical debt in collections was obtained from the Urban Institute Credit Bureau Panel and linked to patient-level data based on patients’ county of residence and year of diagnosis. 
• Associations between medical debt quartiles and stage IV diagnoses and overall survival were assessed, with adjustment for diagnosis year, age, sex, race and ethnicity, insurance status, comorbidities, metropolitan status, county-level Social Deprivation Index, Medically Underserved Area designation, and state of residence. 

TAKEAWAY

• Patients living in counties in the highest quartile of medical debt were more likely to be diagnosed with stage IV disease compared with those in the lowest quartile (odds ratio, 1.079). They also had poorer overall survival (hazard ratio, 1.072), with a statistically significant dose-response relationship (P for trend < .001).
• Across counties, the proportion of adults with medical debt ranged from 0% to 56%. In counties with the lowest levels of debt (0%-12%), 38.8% of patients with cancer were diagnosed with stage I disease and 19.2% with stage IV disease. That compared with rates of 34.4% and 21.2%, respectively, in counties with the highest debt levels (23.1%-56%).
• Patients in counties with the highest levels of medical debt had the poorest 5-year survival rate, at 58.6%. That compared with 66.3% in counties with the lowest levels of debt.
• The dose-response relationship between county-level medical debt and stage at diagnosis, as well as survival, was consistent across all subgroups analyzed — including age groups, race and ethnicity, insurance status, metropolitan status, and comorbidity levels.

IN PRACTICE

“Taken together, our findings suggest that policies and programs that either directly prevent or mitigate medical debt, or that structurally promote economic development in vulnerable communities and thereby strengthen residents’ financial resilience, have the potential to improve access to affordable care and further enhance cancer outcomes and health equity,” the authors of the study wrote.

In a press release, the lead author said, “Future research is needed to evaluate ongoing policies, including those related to medical debt, large federal cuts to Medicaid and the social safety net, and expiration of Marketplace insurance subsidies, and their relationship with cancer care and outcomes.”

SOURCE

This study, led by Xuesong Han, PhD, of the American Cancer Society in Atlanta, was published online in the Journal of the National Comprehensive Cancer Network.

LIMITATIONS

The NCDB is not population-based, which may limit generalizability, and it does not collect cause of death, preventing evaluation of cancer-specific survival in relation to medical debt. Medical debt statistics were based only on consumers with established credit records and may not include some of the most financially vulnerable populations. As with all observational studies, causality cannot be inferred.

DISCLOSURES

The underlying county-level medical debt data were assembled by the Urban Institute with funding from Arnold Ventures. The authors had no relevant disclosures.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.