Who is responsible? A risk-stratified framework for pharmacist accountability in artificial intelligence–assisted managed care

Artificial intelligence (AI)-enabled tools are increasingly integrated into managed care pharmacy workflows, particularly in utilization management and prior authorization processes. Although these systems aim to improve operational consistency and efficiency, federal regulatory guidance and professional standards make clear that coverage and medical necessity determinations must remain grounded in human clinical judgment. As AI tools become part of routine managed care, responsibility for final decisions may become unclear, creating an accountability gap. This article synthesizes federal regulatory guidance and professional pharmacy standards relevant to AI use in health care. We review Centers for Medicare & Medicaid Services requirements, oversight findings from the US Department of Health and Human Services Office of Inspector General, and established pharmacy ethics frameworks. Based on this review, we propose a pharmacist-centered accountability framework for AI-assisted managed care decisions. The framework emphasizes explicit professional responsibility, structured human-in-the-loop review, and documentation practices that support transparency and auditability. Clarifying pharmacist accountability in AI-assisted utilization management can strengthen professional stewardship, enhance workforce readiness, and support responsible innovation in managed care pharmacy.

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Publication Details

Journal
Journal of Managed Care & Specialty Pharmacy
Published
2026-08-25
DOI
https://doi.org/10.18553/jmcp.2026.32.9.1130
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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0.00
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article

Who is responsible? A risk-stratified framework for pharmacist accountability in artificial intelligence–assisted managed care

Chalissa Dibya Iranisha, Emine Gülce Byers
Journal of Managed Care & Specialty Pharmacy
Artificial Intelligence in Healthcare and Education
article

Who is responsible? A risk-stratified framework for pharmacist accountability in artificial intelligence–assisted managed care

Chalissa Dibya Iranisha, Emine Gülce Byers
article en

Abstract

Artificial intelligence (AI)-enabled tools are increasingly integrated into managed care pharmacy workflows, particularly in utilization management and prior authorization processes. Although these systems aim to improve operational consistency and efficiency, federal regulatory guidance and professional standards make clear that coverage and medical necessity determinations must remain grounded in human clinical judgment. As AI tools become part of routine managed care, responsibility for final decisions may become unclear, creating an accountability gap. This article synthesizes federal regulatory guidance and professional pharmacy standards relevant to AI use in health care. We review Centers for Medicare & Medicaid Services requirements, oversight findings from the US Department of Health and Human Services Office of Inspector General, and established pharmacy ethics frameworks. Based on this review, we propose a pharmacist-centered accountability framework for AI-assisted managed care decisions. The framework emphasizes explicit professional responsibility, structured human-in-the-loop review, and documentation practices that support transparency and auditability. Clarifying pharmacist accountability in AI-assisted utilization management can strengthen professional stewardship, enhance workforce readiness, and support responsible innovation in managed care pharmacy.

Journal of Managed Care & Specialty PharmacyVol. 32(9)
University of Rhode Island (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Artificial Intelligence in Healthcare and Education
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Who is responsible? A risk-stratified framework for pharmacist accountability in artificial intelligence–assisted managed care — Chalissa Dibya Iranisha, Emine Gülce Byers · Journal of Managed Care & Specialty Pharmacy (2026) | TGRS Research Map | TGRS