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The Medicaid Rx model: pharmacy-based risk adjustment for public programs.

T Gilmer1, R Kronick, P Fishman

  • 1Department of Family and Preventive Medicine, University of California, San Diego 92093-0622, USA. tgilmer@ucsd.edu

Medical Care
|October 19, 2001
PubMed
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Pharmacy data can complement diagnostic data for better risk adjustment in Medicaid. Combining both data sources improves illness severity assessment, especially for TANF populations.

Area of Science:

  • Health Services Research
  • Health Economics
  • Pharmacoeconomics

Background:

  • Traditional risk adjustment models rely on diagnostic data, but concerns exist regarding its availability and reliability.
  • Pharmacy data presents a potential alternative or complementary method for assessing illness severity and risk adjustment.

Purpose of the Study:

  • To develop and validate a pharmacy-based risk adjustment model for Supplemental Security Income (SSI) and Temporary Assistance for Needy Families (TANF) Medicaid populations.
  • To evaluate the performance of pharmacy data compared to diagnostic data in risk adjustment models.

Main Methods:

  • Developed the Medicaid Rx model, classifying National Drug Codes into risk-assessment categories.
  • Employed pharmacological review and empirical evaluation using data from 1990-1999.

Related Experiment Videos

  • Compared pharmacy and diagnostic classification for three chronic diseases and evaluated model performance using R2 statistics and simulated health plans.

    • Main Results:

    • Pharmacy and diagnostic classifications showed varying abilities in identifying specific chronic diseases.
    • Diagnostic models better predicted expenditures for disabled Medicaid beneficiaries, while pharmacy and diagnostic models performed similarly for TANF beneficiaries.
    • Models integrating both diagnostic and pharmacy data demonstrated superior overall performance.

    Conclusions:

    • Combined pharmacy and diagnostic data yield superior risk adjustment model performance compared to using either source alone, particularly for TANF beneficiaries.
    • Further research is warranted to address concerns about prescribing pattern variations and potential incentives linked to pharmacy use in payment models.