Epidemiology (Cambridge, Mass.) · 2026
Identifying Demographic Predictors of Increased Nonfatal Opioid Overdose Risk Among New York State Medicaid Enrollees After the COVID-19 Pandemic: An Analysis of Heterogeneous Treatment Effects.
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Pamplin John R, Wheeler-Martin Katherine, Perry Allison, Mannes Zachary, Krawczyk Noa, Crystal Stephen, Hasin Deborah S, Martins Silvia S, Shroff Ravi, Cerdá Magdalena, Neill Daniel B
Аннотация
BACKGROUND: Overdose rates in the United States rose dramatically during the coronavirus disease 2019 (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 nonfatal opioid overdose risk after the 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 to 2020. To identify subgroups with the greatest increased risk of nonfatal overdose after the onset of the COVID-19 pandemic, we used a Heterogeneous Treatment Effect-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, the risk of nonfatal opioid overdose increased 22% after the 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 nonfatal overdose risk, respectively.
CONCLUSION: We estimated heterogeneous effects of the onset of the COVID-19 pandemic on nonfatal 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 after complex social events.
METHODS: Data are from a retrospective cohort of 1,021,889 people enrolled in New York State Medicaid from 2019 to 2020. To identify subgroups with the greatest increased risk of nonfatal overdose after the onset of the COVID-19 pandemic, we used a Heterogeneous Treatment Effect-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, the risk of nonfatal opioid overdose increased 22% after the 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 nonfatal overdose risk, respectively.
CONCLUSION: We estimated heterogeneous effects of the onset of the COVID-19 pandemic on nonfatal 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 after complex social events.