aceArtificial intelligence-enabled causal estimate of Medicare drug plan integration in cancer care: A doubly robust machine learning instrumental variable analysis
Background Artificial intelligence (AI) methods are increasingly used to strengthen policy evaluation in managed care pharmacy. Among Medicare beneficiaries with cancer, which is one of the most clinically complex and costly populations, prescription drug coverage is obtained through either integrated Medicare Advantage Prescription Drug plans (MA-PDs) or stand-alone Prescription Drug Plans (PDPs). However, causal evidence of plans' impact remains limited because of nonrandom enrollment. Objective To apply an AI…
AI-enabled Doubly Robust Machine Learning IV analysis adjusted for nonrandom enrollment among Medicare beneficiaries with cancer and showed that apparent higher inpatient and outpatient use under PDP was explained by selection, supporting more accurate evaluation of benefit integration.
Among Medicare beneficiaries with cancer, enrollment in stand-alone Prescription Drug Plans versus integrated Medicare Advantage Prescription Drug plans remained associated with significantly higher Medicare and beneficiary out-of-pocket spending after AI-enabled causal adjustment.
Evidence
- Peer-reviewedJournal of Managed Care & Specialty Pharmacy2026-09-01
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Truvace Impact Record TRV-2026-0958, v1: “Artificial intelligence-enabled causal estimate of Medicare drug plan integration in cancer care: A doubly robust machine learning instrumental variable analysis.” Truvace, 2026-09-01. /record/TRV-2026-0958 (accessed at citation time). sha256 e30472be2291784c…
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