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Using Predictive Modeling to Evaluate Disease Management Financial Impact

Using Predictive Modeling to Evaluate Disease Management Financial Impact. Terry Whitlock, MBA Kenton Johnston, MPH, MS. June 28, 2005. What is Disease Management at BCBST?. CAD, CHF, COPD, Asthma and Diabetes Opt out program External 3 rd party vendor relationship

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Using Predictive Modeling to Evaluate Disease Management Financial Impact

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  1. Using Predictive Modeling to Evaluate Disease Management Financial Impact Terry Whitlock, MBA Kenton Johnston, MPH, MS June 28, 2005

  2. What is Disease Management at BCBST? • CAD, CHF, COPD, Asthma and Diabetes • Opt out program • External 3rd party vendor relationship • Self Insured Groups that participate • Fully Insured Groups for CAD and CHF diseases • FEP Members

  3. What does BCBST look for in DM? • Outcomes Improvement • Improve health of population • Enhance patient satisfaction & care experience • Enhance physician satisfaction & delivery • Improve work force productivity (Indirect Costs) • Reduce total health care costs (Direct Costs)

  4. Impact of Chronic Illness on costs • 78% of Total Medical Costs are attributed to treatment of chronic diseases • Half of Americans report having a chronic disease and these patients cost 3.5 times as much to those without chronic diseases

  5. How do we measure DM impact? • Measuring what would have happened vs. what actually happened is subjective to say the least • Methods used to assess DM impact: • Randomized Control Group studies • Population Based Pre-Post Methodology (Quasi-experimental design) • Predictive Modeling

  6. Why Predictive Modeling? • Predictive Modeling refers to the process of finding rules (models) for predicting an event from prior patterns within a given time frame and applying these rules to current data in order to predict a future event • Helps us account for Regression to the mean • High cost cases in a base year becoming lower cost in subsequent years as well as normal cases in a base year becoming outlier cases in subsequent years

  7. Population based Pre-Post Methodology

  8. Predictive Modeling

  9. Predictive Modeling w/Adjustments

  10. Conclusions of DM Evaluations • A statistically valid predictive model should be incorporated in lieu of randomized control group. • Adjustments (inflation factors, inaccuracy of predictive models, etc.) should be made to model. • Predictive scores and/or illness burdens should be incorporated into initial disease management patient identification and stratification process to improve impactibility.

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