A pharmacist-overseen, artificial intelligence–enabled model for provider-side prior authorization: From burden to opportunity (PAVE-1)

Prior authorization (PA) imposes substantial administrative burdens on clinicians, contributing to burnout, delayed care, and excess health care spending. Artificial intelligence (AI) is emerging as a tool to automate PA tasks in managed care pharmacy, yet concerns persist regarding transparency, bias, and overreliance on autonomous systems. This is particularly true in payer-deployed AI systems that may deny claims without adequate clinical review. This viewpoint proposes a pharmacist-overseen, AI-enabled system designed for provider organizations and health systems as an optimal model, integrating clinical expertise across the AI system's design, triage logic, clinical review, and continuous improvement to ensure clinical rigor and operational efficiency. A conceptual workflow illustrates the AI system handling routine data extraction and submissions while routing complex cases to pharmacists, who verify appropriateness against guidelines and payer criteria. Benefits could include reduced prescriber workload, higher first pass approval rates, and scalable PA management, aligning with Centers for Medicare & Medicaid Services interoperability mandates. Collaborative implementation among payers, pharmacy benefit managers, providers, and vendors, supported by targeted research, could advance PA's evolution from barrier to enabler of value-based care.

Authors

Institutions

Publication Details

Journal
Journal of Managed Care & Specialty Pharmacy
Published
2026-08-25
DOI
https://doi.org/10.18553/jmcp.2026.32.9.1114
Primary Topic
Pharmaceutical Practices and Patient Outcomes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A pharmacist-overseen, artificial intelligence–enabled model for provider-side prior authorization: From burden to opportunity (PAVE-1)

Rachel Reise, Jorge A. Valedon Navarro
Journal of Managed Care & Specialty Pharmacy
Pharmaceutical Practices and Patient Outcomes
article

A pharmacist-overseen, artificial intelligence–enabled model for provider-side prior authorization: From burden to opportunity (PAVE-1)

Rachel Reise, Jorge A. Valedon Navarro
article en

Abstract

Prior authorization (PA) imposes substantial administrative burdens on clinicians, contributing to burnout, delayed care, and excess health care spending. Artificial intelligence (AI) is emerging as a tool to automate PA tasks in managed care pharmacy, yet concerns persist regarding transparency, bias, and overreliance on autonomous systems. This is particularly true in payer-deployed AI systems that may deny claims without adequate clinical review. This viewpoint proposes a pharmacist-overseen, AI-enabled system designed for provider organizations and health systems as an optimal model, integrating clinical expertise across the AI system's design, triage logic, clinical review, and continuous improvement to ensure clinical rigor and operational efficiency. A conceptual workflow illustrates the AI system handling routine data extraction and submissions while routing complex cases to pharmacists, who verify appropriateness against guidelines and payer criteria. Benefits could include reduced prescriber workload, higher first pass approval rates, and scalable PA management, aligning with Centers for Medicare & Medicaid Services interoperability mandates. Collaborative implementation among payers, pharmacy benefit managers, providers, and vendors, supported by targeted research, could advance PA's evolution from barrier to enabler of value-based care.

Journal of Managed Care & Specialty PharmacyVol. 32(9)
University of Florida Health (US), University of Florida (US)
Openalex Percentile: Top 13%
Pharmaceutical Practices and Patient Outcomes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.