| Description |
Predictive Modeling in health care is a process involving assessment & adjustment of risk & behavior, applied to a given population based upon available data for purposes of stratifying that population according to their future probabilities of incurring a given outcome or behavior. The purpose of Predictive Modeling is to risk stratify a population to identify individual opportunities for intervention or action before the projected outcome as occurred.
Predictive Modeling requires an existing data repository, in which data is mined, & selection of a specific modeling tool to apply to the historical timeframe to predict outcomes for an alternative timeframe. Traditional data sources may include individual demographics, pharmacy & medical claims data, lab values, health risk assessment data, & other clinical data.
The Predictive Modeling Web Summit provides a unique means to obtaining current trends, issues & solutions on key predictive modeling topics from leading national experts.
Live Webinar & Audio Conference
• Brian Day, Ed.D., Director, Advanced Analytics, Highmark, Inc., will discuss "Highmark Blue Cross Blue Shield's perspectives on Predictive Modeling applications"
• Chris Birkmeyer, COO and Practice Leader, Solucia Inc., will discuss "Beyond Risk: Incorporating intervenability into predictive models"
• Rong Yi, PhD, Senior Scientist, DxCG - A Division of Urix, will discuss "Risk Adjustment and Predictive Modeling for Medicaid"
Podcasts & Companion Presentations
Additional downloadable Podcast recordings will be available 24/7 to attendees, averaging around 15 minutes in length. Companion presentations related to each Podcast discussion are also available for downloading.
• Swati Abbott, President, MEDai, discussing "Use of predictive modeling to bridge the gap among payors, physicians, & patients"
• Vincent Kane, FSA, MAAA, Research Scientist, DxCG, discussing "Using predictive modeling to simulate Health Savings Account performance for the chronically ill"
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