“Developing a risk prediction engine for relapse in opioid use disorder”

This Triangle CERSI project, which includes a collaboration between Duke University, University of North Carolina, and the Digital Medicine Society (DiMe), will build a protocol for a tool that uses data from digital sensor technologies, like wearables, to predict when people affected by OUD might relapse. Investigators aim to generate a scientific plan to use consumer technologies and the data they collect to predict relapse and to inform early-intervention strategies to provide every person affected by OUD with the care they need, when they need it most.