Abstract

6548 Background: As the result of expansions associated with the Affordable Care Act (ACA), one in five Americans are now insured through Medicaid. Despite overall increases, access to care for Medicaid-insured patients with cancer may be limited by facilities due to lower reimbursement and administrative burden. We aimed to directly assess facility-level acceptance of Medicaid patients with a new diagnosis of cancer. Methods: We performed a cross-sectional secret shopper study to evaluate access to cancer care for colorectal, breast, urologic, and skin cancer at Commission on Cancer (CoC) accredited hospitals. We studied the relationship between Medicaid access and facility-level characteristics assessed through American Hospital Association and Center for Medicare and Medicaid Service data using univariable statistics and multivariable logistic regression. Results: Among 334 CoC facilities contacted, the overall rate of Medicaid acceptance for at least one investigated cancer type was 99% (n = 331). However, we identified hospital-level variation in Medicaid acceptance across cancer types, where Medicaid acceptance for colorectal, breast, urologic, and skin cancer was 90%, 96%, 87%, and 80%, respectively. Of the hospitals that accepted Medicaid, 2% accepted Medicaid for one cancer type, 8% for two, 21% for three, and 68% for all four cancer types. In multivariable logistic regression, odds of Medicaid acceptance were lowest in comprehensive community cancer centers (p < 0.05 for colorectal and urologic cancer) and for-profit designated facilities (p < 0.05 for urologic and skin cancer) (Table). Hospitals in states with Medicaid expansion were also more likely to accept Medicaid for urologic (OR: 2.5, 95% CI: 1.2-5.2) and breast (OR: 12.8, 95% CI: 2.7-60.2) cancer care. Conclusions: Access disparities persist for patients with Medicaid, with acceptance rates differing substantially within and between facilities. Facility-level differences in Medicaid access among CoC facilities are notable given the use of hospital registry data to estimate ACA-related effects.[Table: see text]

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