Validity of competing algorithms to identify people with HIV in Medicaid administrative claims: a statewide analysis
Case identification algorithms have good performance when applied in a population-based sample of claims data with low HIV prevalence and using multiple code types. Trade-offs between discriminative and predictive ability suggest algorithms should be tailored to use.
Authors
- Karen Ingersoll (ORCID: https://orcid.org/0000-0001-8115-2548)
- Rebecca Dillingham (ORCID: https://orcid.org/0000-0001-9748-1215)
- Michael J. Stirratt (ORCID: https://orcid.org/0000-0001-5243-9312)
- Rachel Stallings
- Jessica S. Kiernan (ORCID: https://orcid.org/0000-0002-7371-3218)
- Kathy K. Byrd (ORCID: https://orcid.org/0000-0002-9818-5634)
- Bassam Dahman (ORCID: https://orcid.org/0000-0001-7209-5369)
- April D. Kimmel (ORCID: https://orcid.org/0000-0002-3966-8476)
- Andrew Mitchell (ORCID: https://orcid.org/0000-0002-3946-4094)
- Zhongzhe Pan (ORCID: https://orcid.org/0009-0006-2439-9847)
- Rose S. Bono (ORCID: https://orcid.org/0000-0002-8980-5678)
Institutions
- Centers for Disease Control and Prevention (US)
- National Institutes of Health (US)
- Economic Research Service (US)
- Virginia Commonwealth University (US)
- Martha Jefferson Hospital (US)
- Office of Readiness and Response (US)
- National Institute of Mental Health (US)
- Department of Health Services (US)
- University of Virginia (US)
Publication Details
- Journal
- AIDS
- Published
- 2025-10-07
- DOI
- https://doi.org/10.1097/qad.0000000000004362
- Primary Topic
- HIV, Drug Use, Sexual Risk
- Type
- article
- Field-Weighted Citation Impact
- 0.00