A group of Duke Health researchers recently shared their insights on approaches to managing the complex issues that are emerging as “algorithmic medicine” increasingly becomes part of clinical care at hospitals and health systems. The authors, who comprise faculty and staff from Duke AI Health, Duke Health Technology Solutions, the Duke Institute for Health Innovation, and other physicians and researchers from Duke University and Duke University Health System, published an account of their approach to evaluating and monitoring the use of algorithmic predictive models at Duke Health hospitals and clinics. The article, titled “A framework for the oversight and local deployment of safe and high-quality prediction models,” was published on May 31 in the Journal of the American Medical Informatics Association (JAMIA). It showcases the processes and procedures by which an expert group at Duke Health known as Algorithm-Based Clinical Decision Support (ABCDS) Oversight reviews, approves, and manages predictive models intended for use in patient care settings.
