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