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Examining Unfairness in CMS's Hierarchical Condition Categories Score and the Potential Impact on Health Systems and Health Plans Serving Minorities

Grant Details

Grantee Organization
Trustees of the University of Pennsylvania

Principal Investigator
Amol Navathe, M.D., Ph.D.

Term
3/1/22 - 12/1/23

Award Amount
$200,000

Approval Year

Related Program
Health Care Delivery System Reform

Topics
Medicare

Grant Details

Grantee Organization
Trustees of the University of Pennsylvania

Principal Investigator
Amol Navathe, M.D., Ph.D.

Term
3/1/22 - 12/1/23

Award Amount
$200,000

Approval Year

Related Program
Health Care Delivery System Reform

Topics
Medicare

This project will: 1) examine unfairness in the Centers for Medicare and Medicaid Services' Hierarchical Condition Categories (HCC) score by race/ethnicity, urban/rural status, and socioeconomic status; 2) determine whether integrating individual or area-level metrics into predictive models would mitigate algorithmic unfairness in the HCC score; and 3) quantify the impact of a fairer HCC score on risk-adjusted reimbursements to health plans and accountable care organizations that disproportionately serve people of color, rural, or socioeconomically disadvantaged patients. For these analyses, the team would use Medicare claims from 2015–2019 linked to Medicare Current Beneficiary Survey (MCBS) data.

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