Current Use and Evaluation of Predictive Models in US Hospitals
Session Description
Effective evaluation and governance of predictive models, particularly those driven by artificial intelligence (AI) and machine learning (ML), are essential to ensure use of fair, appropriate, valid, effective, and safe models. While there is a general sense that some organizations are better positioned to govern AI than others, there is limited data on how healthcare delivery organizations nationwide are pursuing AI governance and evaluation. More detail will be important to ensure well-targeted policy and practice interventions promote effective use of models. In this webinar, we will present data on how US hospitals are currently using predictive models and evaluating them for common concerns like validity and bias.
Video Recording
Speakers
Paige Nong, PhD
Dr. Nong’s research focuses on health information technology and its social implications, with an emphasis on structural inequities and racism. She is especially interested in how health IT relates to patient trust and engagement. She draws on sociology and public health to understand 1) patient experiences of data collection and technology use in healthcare and 2) how health systems make decisions about these technologies.
Jordan Everson, PhD, MPP
Jordan Everson, PhD, MPP, is a public health analyst at the Office of the National Coordinator for Health Information Technology (ONC) within the Department of Health and Human Services. Across a range of analytic projects, Dr. Everson has led surveys of patients, physicians, and hospital leaders, and has used electronic health record data and medical claims data to assess the use and impact of health information technology. He has published widely on health information technology and interoperability in the peer-reviewed literature.
Prior to joining ONC, Dr. Everson was an assistant professor in Vanderbilt University Medical Center’s Department of Health Policy. Dr. Everson holds a PhD in health services, organizations, and policy from the University of Michigan. a Master of Public Policy from Georgetown University, and a BA from Duke University.
