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Related Experiment Videos

Predicting risk selection following major changes in Medicare.

Steven D Pizer1, Austin B Frakt, Roger Feldman

  • 1Health Care Financing & Economics, US Department of Veterans Affairs, Boston, MA, USA. pizer@bu.edu

Health Economics
|June 9, 2007
PubMed
Summary
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Statistical models accurately predicted the market share and stability of new Medicare prescription drug plans (PDPs). These models, using historical data, forecast substantial adverse selection but stable enrollment and premiums for PDPs.

Area of Science:

  • Health economics
  • Health policy analysis
  • Statistical modeling in healthcare

Background:

  • The Medicare Modernization Act of 2003 introduced novel private insurance plan types within Medicare.
  • Significant uncertainty surrounded the market prospects of these new Medicare plan types.
  • The Medicare Current Beneficiary Survey provides historical data relevant to Medicare insurance enrollment.

Purpose of the Study:

  • To demonstrate the utility of statistical models and historical data for predicting the performance of new Medicare plan types.
  • To forecast market share, risk selection, and stability for stand-alone Medicare prescription drug plans (PDPs).
  • To establish a foundation for analyzing proposed Medicare program modifications.

Main Methods:

  • Estimation of a consumer choice model across existing Medicare insurance plans.

Related Experiment Videos

  • Modification of data to incorporate Medicare prescription drug plans (PDPs).
  • Prediction of individual beneficiary enrollment probabilities for each plan type.
  • Calculation of mean-adjusted actual spending by plan type.

    • Main Results:

    • Statistical models accurately predicted the experience of new Medicare plan types.
    • Substantial adverse selection into PDPs was predicted.
    • Enrollment and premiums for PDPs were predicted to be stable.
    • Predictions showed strong correspondence with actual 2006 experience.

    Conclusions:

    • Statistical modeling using historical data is a reliable method for forecasting the outcomes of new Medicare insurance plans.
    • The findings support the analysis of program modifications by providing accurate predictive capabilities.
    • The study validates the predictive power of models for market share, risk selection, and stability in Medicare.