MDL-03 - Reducing the Pain of Diversion Surveillance: Leveraging Machine Learning to Optimize Organizational Processes

Drug diversion has been a longstanding issue in the healthcare realm with up to 15% of healthcare workers engaged in illicit drug use, but there are now additional factors to consider like the worsening opioid epidemic, the impact of the COVID-19 pandemic, staff burnout, and staffing shortages. For over half of diversion cases, incidents occur for a year or more before detection. Advances have been made over the last few years in available surveillance tools to identify diversion sooner, with some providing real-time feedback to leaders. This session will review best practices on preventing diversion of controlled substances, share lessons learned from the creation of a robust diversion surveillance program leveraging artificial intelligence, corresponding metric development and reporting for stewardship efforts, and introduction of a standardized corrective action plan focused on appropriate controlled substance handling.