Access to addiction treatment is not evenly distributed across geography or demographics — and for Medicaid enrollees battling opioid use disorder, where you live and what race you are may determine whether you receive evidence-based medication at all. This distinction matters enormously given that buprenorphine, methadone, and naltrexone together represent the gold standard of opioid use disorder (OUD) care, substantially reducing overdose mortality when consistently accessed.
This cross-sectional analysis drew on Medicaid data from 10 states participating in the Medicaid Outcomes Distributed Research Network in 2021, covering adults aged 18–64 not dually enrolled in Medicare. Geographic access to medications for opioid use disorder (MOUD) was operationalized at the zip-code level as the density of prescribers and methadone programs reachable within a 15-minute drive per 100 Medicaid enrollees. The researchers then tested whether above-median provider availability modified racial and ethnic disparities in buprenorphine, methadone, and naltrexone utilization — probing whether proximity to care translates equally across groups.
The findings enter a well-documented but still troubling literature: racial disparities in MOUD access have been flagged repeatedly since buprenorphine's federal approval in 2002, yet structural explanations remain contested. Prior work has implicated prescriber bias, insurance authorization hurdles, and pharmacy stocking inequities. What this study adds is a zip-code-level geographic lens, isolating proximity as one testable mechanism. The critical question it raises — whether closing the geographic gap actually closes the racial gap — reflects a debate central to health equity policy. A key limitation is the cross-sectional design, which cannot establish causation; unmeasured confounders such as patient-level stigma, transportation barriers beyond drive time, or prescriber-level racial concordance remain unaccounted for. The 10-state sample also limits national generalizability. Still, for health systems and policymakers, this is a data-dense, methodologically rigorous contribution that quantifies one structural lever in a complex disparity — making it incrementally but meaningfully important.