The study published June 1 in Lancet Digital Health analyzed nearly 14,000 Medicaid recipients in Pennsylvania and Arizona who had opioid overdoses between 2013 and 2018. The tool used 284 potential predictors from pharmaceutical and healthcare claims data.
A machine learning algorithm strongly predicted the three-month risk of opioid overdose for the beneficiaries, the researchers wrote, and could be used to target patients for interventions.
Future validation research should look at other state Medicaid programs and geographic regions, such as the Midwest and South, according to the researchers from the University of Florida, University of Pittsburgh, University of Arizona, University of Utah and Carnegie Mellon University.
Funding for the study came from National Institutes of Health, National Institute on Drug Abuse and National Institute on Aging.
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