Stimulant Overdose Prediction Model for Medicaid-Insured Persons

Can a prediction model using individual- and area-level characteristics predict emergency department (ED) treatment and/or hospitalization for a stimulant-involved overdose ?This case-cohort study using Medicaid data for 78 795 Medicaid enrollees (2016-2020) found that a previous diagnosis of substance use disorder and certain area-level sociodemographic variables effectively predicted ED and/or hospital admission risk for overdose involving cocaine, methamphetamines, ecstasy, or other psychostimulants. The prediction models showed good calibration and excellent discrimination in predicting stimulant-involved overdose risk.These findings indicate that prediction models using Medicaid and other available data can identify those at highest risk for cocaine- and methamphetamines-involved overdose, with or without opioid involvement.

Corresponding Author: Sean Hennessy, PharmD, PhD, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, 803 Blockley Hall, Philadelphia, PA 19104 (hennessy@pennmedicine.upenn.edu).

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