Predicting self-administered biologic nonadherence in Medicare fee-for-service beneficiaries with inflammatory bowel disease using machine learning models
Machine learning models trained on Medicare fee-for-service claims data had fair predictive performance identifying nonadherent dispenses. The bagging model, which minimizes false negatives, may be most appropriate for future clinical decision support tools.
Authors
- Jeffery Talbert (ORCID: https://orcid.org/0000-0002-4304-5167)
- Terrence A. Barrett (ORCID: https://orcid.org/0000-0001-6428-3271)
- C. Rhudy
- Michael J. Wesley (ORCID: https://orcid.org/0000-0003-1545-3865)
- David W. Fardo (ORCID: https://orcid.org/0000-0002-7207-4696)
- Courtney Perry (ORCID: https://orcid.org/0000-0001-6177-3128)
- Cody Bumgardner
Institutions
- University of Kentucky HealthCare (US)
- University of Kentucky (US)
Publication Details
- Journal
- Journal of Managed Care & Specialty Pharmacy
- Published
- 2025-12-24
- DOI
- https://doi.org/10.18553/jmcp.2026.32.1.27
- Primary Topic
- Healthcare Policy and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00