In the United States, 2.7 million people ages 12 or older reported suffering from opioid use disorder (OUD) in 2020, with relapse rates of 65-70%. In addition, 75% of overdose deaths in the U.S. are due to opioids and the cost of the epidemic is estimated at $1.5 trillion.
Project Description and Goals
This 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. Our project will 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.
Anticipated Outcomes
At the conclusion of this project there will be an evidence based, scientific plan to build an equitable, data-driven tool to predict relapse in a person living with OUD. This tool offers a low burden, high reach, and scalable solution for preventing lapses & relapses for all individuals with OUD, offering a pathway to improve care for all people affected by OUD.
