{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T23:29:54Z","timestamp":1782516594930,"version":"3.54.5"},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2023,2,21]],"date-time":"2023-02-21T00:00:00Z","timestamp":1676937600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["UL1 TR001450"],"award-info":[{"award-number":["UL1 TR001450"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,4,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Prior authorization (PA) may be a necessary evil within the healthcare system, contributing to physician burnout and delaying necessary care, but also allowing payers to prevent wasting resources on redundant, expensive, and\/or ineffective care. PA has become an \u201cinformatics issue\u201d with the rise of automated methods for PA review, championed in the Health Level 7 International\u2019s (HL7\u2019s) DaVinci Project. DaVinci proposes using rule-based methods to automate PA, a time-tested strategy with known limitations. This article proposes an alternative that may be more human-centric, using artificial intelligence (AI) methods for the computation of authorization decisions. We believe that by combining modern approaches for accessing and exchanging existing electronic health data with AI methods tailored to reflect the judgments of expert panels that include patient representatives, and refined with \u201cfew shot\u201d learning approaches to prevent bias, we could create a just and efficient process that serves the interests of society as a whole. Efficient simulation of human appropriateness assessments from existing data using AI methods could eliminate burdens and bottlenecks while preserving PA\u2019s benefits as a tool to limit inappropriate care.<\/jats:p>","DOI":"10.1093\/jamia\/ocad016","type":"journal-article","created":{"date-parts":[[2023,2,21]],"date-time":"2023-02-21T19:31:27Z","timestamp":1677007887000},"page":"989-994","source":"Crossref","is-referenced-by-count":16,"title":["Could an artificial intelligence approach to prior authorization be more human?"],"prefix":"10.1093","volume":"30","author":[{"given":"Leslie A","family":"Lenert","sequence":"first","affiliation":[{"name":"Biomedical Informatics Center, Medical University of South Carolina , Charleston, South Carolina, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steven","family":"Lane","sequence":"additional","affiliation":[{"name":"Health Gorilla , Mountain View, California, 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