Researcher: Soumya Sen (Information and Decision Sciences Department, Carlson School of Management)
Substance abuse and addiction to alcohol, tobacco, and other drugs have a significant and costly impact on the health and well being of residents of our state. In partnership with the Hazelden Betty Ford Foundation of Center City, MN, we propose to take a data-driven approach – using machine learning and data analytics on electronic health records of patients suffering from substance use disorder – to help care providers improve their understanding of the patient population, predict risk of relapse, and design better treatment plans. Our research will study how different factors (e.g., age, gender, type and combination of substances used) impact relapse to drugs or alcohol throughout the course of different developmental periods, and help facilitate the identification of the best early treatment options for patients. Our findings will provide real-world data based guidance for addiction treatment and inform new policies on how insurers approve coverage for substance abuse treatments.