Predicting clinical risk is an important part of healthcare and can inform decisions about treatments, preventive interventions, and provision of extra services. The field of predictive models has been revolutionized over the past two decades by electronic health record data; the ability to link such data with other demographic, socioeconomic, and geographic information; the availability of high-capacity computing; and new machine learning and artificial intelligence methods for extracting insights from complex datasets. These advances have produced a new generation of computerized predictive models, but debate continues about their development, reporting, validation, evaluation, and implementation. In this review we reflect on more than 10 years of experience at the Veterans Health Administration, the largest integrated healthcare system in the United States, in developing, testing, and implementing such models at scale. We report lessons from the implementation of national risk prediction models and suggest an agenda for research.
Dr. Atkins is the former Director of VA’s Health Services Research and Development (HSRD) Service. His interests focus on the intersection between research evidence, clinical and public policy, and health system improvement. He has written widely about standards of evidence and the role of evidence in guidelines, performance measures, policy and system change. As Director at HSR&D, he oversaw a more than $115 million intramural health services research program, with more than 600 funded investigators and 245 ongoing research projects aimed at improving the health and care of Veterans. Dr. Atkins has also served as Director of VA/HSR&D's Quality Enhancement Research Initiative (QUERI), VHA’s Acting Chief Research and Development Officer, Chief Medical Officer at the Center for Outcomes and Evidence at the Agency for Healthcare Research and Quality (AHRQ), and as a Senior Advisor for the U.S. Preventive Services Task Force. Dr. Atkins received his M.D. from Yale University, is Board certified in Internal Medicine, and has a Masters of Public Health in Epidemiology from the University of Washington, where he complete a NRSA Fellowship in Primary Medicine.
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