PDMP Overdose Data to Action (OD2A) Opioid Overdose Surveillance

PI: Walid Gellad, MD, MPH
Funding Source: CDC
March 2020 - August 2023

This project links Pennsylvania’s prescription drug monitoring program data with fatal overdose records, EMS-administered naloxone, and other data to build a real-time machine learning model that identifies individuals at high risk of opioid overdose. The study team partnered with the Pennsylvania Department of Health and researchers from Carnegie Mellon University to strengthen data integration and enhance model development and usability.

Read published results from this work

Development and validation of an overdose risk prediction tool using prescription drug monitoring program data
Walid F. Gellad, Qingnan Yang, Kayleigh M. Adamson, Courtney C. Kuza, Jeanine M. Buchanich, Ashley L. Bolton, Stanley M. Murzynski, Carrie Thomas Goetz, Terri Washington, Michael F. Lann, Chung-Chou H. Chang, Katie J. Suda, Lu Tang
Drug and Alcohol Dependence, March 29, 2023

Static Algorithm, Evolving Epidemic: Understanding the Potential of Human-AI Risk Assessment to Support Regional Overdose Prevention
Venkatesh Sivaraman, Yejun Kwak, Courtney Kuza, Qingnan Yang, Kayleigh Adamson, Katie Suda, Lu Tang, Walid Gellad, Adam Perer
Proceedings of the ACM on Human-Computer Interaction, February 14, 2025

Buprenorphine Dispensing in Pennsylvania During the COVID-19 Pandemic, January to October 2020
Rohan Chalasani BA, Jared M. Shinabery MPH, Carrie Thomas Goetz PhD, Chung-Chou H. Chang PhD, Qingnan Yang MS, MA, Katie J. Suda PharmD, MS, FCCP, & Walid F. Gellad MD, MPH
Journal of General Internal Medicine, August 10, 2021