How to Learn in "The Learning Healthcare System"

National Library of Medicine Informatics Lecture Series The Institute of Medicine has argued for more than 20 years that we should view every patient interaction as an (uncontrolled) experiment, and learn from its outcome. Dr. Szolovits has been a participant in numerous collaborative projects, trying to apply this method to data about a broad range of patients suffering from conditions such as arthritis, cardiovascular disease, diabetes, inflammatory bowel disease, autism, depression. In this lecture, he will review some of the methodological challenges he has encountered and the hard-won lessons he has learned. These include the careful formulation of study goals, the importance of open data, what kinds of models to build, how to extract meaning from narrative text, and how to incorporate non-traditional sources of data into a research protocol. Dr. Szolovits will also describe a largely unsuccessful effort to ease the data collection burden in health care by having computerized speech understanding systems listen to and analyze conversations between doctors and patients. Air date: 11/5/2014 2:00:00 PM
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