Algorithms to Improve Fairness in Medicare Risk Adjustment
Results of this study suggest that constrained regression and postprocessing can incorporate fairness objectives into the Medicare risk adjustment algorithm with minimal reduction in overall fit. These feasible changes to the Medicare risk adjustment algorithm could be considered by policymakers aiming to address health care disparities through payment system reform.
Authors
- Sherri Rose (ORCID: https://orcid.org/0000-0002-9076-8472)
- Marissa B Reitsma (ORCID: https://orcid.org/0000-0001-7276-4876)
- Thomas G. McGuire
Institutions
- Harvard University (US)
- Stanford University (US)
Publication Details
- Journal
- JAMA Health Forum
- Published
- 2025-08-29
- DOI
- https://doi.org/10.1001/jamahealthforum.2025.2640
- Primary Topic
- Healthcare Policy and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Laura and John Arnold Foundation
- National Institutes of Health
- School of Medicine, Stanford University