Identifying demographic predictors of increased non-fatal opioid overdose risk among New York State Medicaid enrollees following the COVID-19 pandemic: an analysis of heterogeneous treatment effects

BACKGROUND: Overdose rates in the U.S. rose dramatically during the COVID-19 pandemic. Well-documented racial and sociodemographic inequities in the impact of the pandemic suggest the potential for similar inequities for overdose. Our objective was to identify subgroups of New York State Medicaid enrollees who experienced the greatest increases in non-fatal opioid overdose risk following onset of the COVID-19 pandemic. METHODS: Data are from a retrospective cohort of 1,021,889 people enrolled in New York State Medicaid from 2019-2020. To identify subgroups with the greatest increased risk of non-fatal overdose following onset of the COVID-19 pandemic, we used Heterogeneous Treatment Effect (HTE)-Scan, a novel machine learning method developed for accurate and computationally efficient discovery of heterogeneous treatment effects in complex data. RESULTS: In the total sample, risk of non-fatal opioid overdose increased 22% after onset of the pandemic. We also identified two subgroups with elevated risk relative to the total sample: subgroup 1 (Black and Hispanic males aged 45-64 years old with no baseline documentation of opioid use disorder (OUD); N = 53,065) and subgroup 2 (people aged 45-64 years old with documented aged/blind/disabled status and no baseline documentation of OUD; N = 73,694). These subgroups experienced a 54% and 57% increase in non-fatal overdose risk, respectively. CONCLUSIONS: We estimated heterogeneous effects of onset of the COVID-19 pandemic on non-fatal overdose, with elevated risks estimated for older working-aged, structurally disadvantaged adults without documented OUD. These findings illustrate the importance of structural factors in driving heterogeneous risk of overdose following complex social events.