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  1. Home
  3. Use Of Patient Health Survey Data For Risk Adjustment To Limit Distortionary Coding Incentives In Medicare.
  1. Home
  3. Use Of Patient Health Survey Data For Risk Adjustment To Limit Distortionary Coding Incentives In Medicare.

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Use Of Patient Health Survey Data For Risk Adjustment To Limit Distortionary Coding Incentives In Medicare.

J Michael McWilliams1, Gabe Weinreb2, Mary Beth Landrum3

  • 1J. Michael McWilliams (mcwilliams@hcp.med.harvard.edu), Harvard University and Brigham and Women's Hospital, Boston, Massachusetts.

Health Affairs (Project Hope)
|January 6, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

A new hybrid risk score using survey data and fewer Hierarchical Condition Categories (HCCs) could improve Medicare Advantage and ACO payments. This approach mitigates coding incentives and promotes equitable, efficient care delivery.

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Area of Science:

  • Health economics
  • Health services research
  • Medical informatics

Background:

  • Current Medicare Advantage and Accountable Care Organization (ACO) risk adjustment relies on the Hierarchical Condition Categories (HCC) model.
  • The HCC model's reliance on coded diagnoses presents vulnerabilities to manipulation by risk-bearing entities for financial gain.

Purpose of the Study:

  • To evaluate a hybrid risk adjustment model incorporating survey data on health status.
  • To assess the potential of this hybrid model to mitigate coding incentives and improve payment allocation.

Main Methods:

  • Utilized existing survey data on health status as less manipulable inputs.
  • Developed a hybrid risk score combining survey data with a reduced set of HCCs.
  • Analyzed the impact on risk-selection, payment efficiency, and equity.

Main Results:

  • The hybrid model mitigates coding incentives and modestly lessens risk-selection incentives.
  • It strengthens payment incentives for efficient care delivery.
  • Payment allocation across ACOs becomes more efficient based on population health markers, supporting equity goals.

Conclusions:

  • A hybrid risk score using survey data offers a promising strategy to enhance risk adjustment in Medicare Advantage and ACO programs.
  • Despite challenges like sampling error and nonresponse, the approach is feasible and warrants further development.
  • This method can lead to more equitable and efficient healthcare payments.