“Machine learning models that use administrative data appear to be a valuable and feasible tool for identifying more accurately and efficiently individuals at high risk of opioid overdose," notes CP3 Director Walid Gellad. Health IT Analytics featured new work published in JAMA Network Open from Dr. Gellad, Dr. Jenny Lo-Ciganic, and their team. The group developed a new machine learning algorithm that is more effective than previous methods for determining risk for opioid overdose among Medicare beneficiaries.