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

A core problem with the current risk-adjustment system in Medicare Advantage and accountable care organization (ACO) programs--the Hierarchical Condition Categories (HCC) model--is that the inputs (coded diagnoses) can be influenced for gain by risk-bearing plans or providers. Using existing survey...

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Publicado en:Health Affairs Vol. 44; no. 1; pp. 48 - 58
Autores principales: McWilliams, J. Michael, Weinreb, Gabe, Landrum, Mary Beth, Chernew, Michael E.
Formato: research tables/charts Journal Article
Publicado: Health Affairs Publishing, LLC Jan2025
Acceso en línea:Ver este registro en EBSCOhost
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        10.1377/hlthaff.2023.01351
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        atl: Use Of Patient Health Survey Data For Risk Adjustment To Limit Distortionary Coding Incentives In Medicare.
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          McWilliams, J. Michael
          Weinreb, Gabe
          Landrum, Mary Beth
          Chernew, Michael E.
        affil: Harvard University and Brigham and Women's Hospital, Boston, Massachusetts
      sug:
        subj:
          Fee for Service Plans
          Medicare
          Accountable Care Organizations
          International Classification of Diseases
          Coding
          Reimbursement, Incentive
          Health Care Costs
          Health Services Needs and Demand
          Human
          United States
          Cross Sectional Studies
          Concept Analysis
          Comparative Studies
          Self Report
          Health Status
          Functional Status
          Chronic Disease
          Mortality
          Hospitalization
          Drugs, Prescription
          Medication Management
          Health Expenditures
          Primary Health Care
          Activities of Daily Living
          Regression
          Descriptive Statistics
          Practice Patterns
          Prospective Payment System
          Health Resource Allocation
          Health Services Accessibility
          Funding Source
      ab: A core problem with the current risk-adjustment system in Medicare Advantage and accountable care organization (ACO) programs--the Hierarchical Condition Categories (HCC) model--is that the inputs (coded diagnoses) can be influenced for gain by risk-bearing plans or providers. Using existing survey data on health status (which provide less manipulable inputs), we found that the use of a hybrid risk score drawing from survey data and a scaled-back set of HCCs would, in addition to mitigating coding incentives, modestly lessen risk-selection incentives, strengthen payment incentives to deliver efficient care, allocate payment across ACOs more efficiently according to markers of population health that are not as affected by practice patterns or coding efforts, and redistribute payment in a manner that supports equity goals. Although sampling error and survey nonresponse present challenges, analyses suggest that these should not be prohibitive. Overall, our proof-of-concept analysis suggests that using survey data to improve riskadjustment performance is a promising strategy that merits further development.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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