Clinician Use of an Artificial Intelligence–Enabled Clinical Information Platform

Abstract

Importance Despite growing interest in the use of artificial intelligence (AI) in medicine, empirical evidence on how clinicians use these tools is limited. Objective To characterize clinician use of an AI-enabled clinical information platform, the distribution of use across the clinical workforce, and the purpose of submitted queries. Design, Setting, and Participants This cross-sectional study analyzed clinicians with National Provider Identifier–verified accounts of a commonly used AI-enabled clinical information platform, OpenEvidence, from January 1, 2024, through June 30, 2026. A large language model was used to classify the clinical purpose and topic areas of a stratified random sample of 38.8 million queries. Main Outcomes and Measures The number of active users and clinical queries, the share of queries relative to representation in the national workforce, and the clinical purpose and topic of queries were examined. Results Overall, 952 008 clinicians (58.5% female), including 556 200 physicians, submitted 271 million queries during the 2.5-year study period. Monthly active users increased from 355 in January 2024 to 703 265 in June 2026, and average monthly queries per active user rose from 18.0 to 39.5. Nurse practitioners (44.5) and physician assistants (44.5) submitted more queries per active user-month than physicians (37.1). A higher share of queries relative to the national workforce was submitted by physicians within a decade of graduation (use ratio, 2.54) and residents and fellows (1.84). Use was also higher than average among physicians specializing in oncology and hematology (use ratio, 2.00), internal medicine (1.88), and family medicine (1.80), but lower in procedural and diagnostic specialties (ophthalmology, 0.23; radiology, 0.24; orthopedics, 0.24). Most queries addressed clinical decision-making (51.9%), particularly treatment and management (33.1%), whereas diagnosis accounted for 13.9% of queries. Queries addressing topics outside physicians’ own specialties ranged from 35% among oncologists and hematologists to 88% among emergency department physicians. Conclusions and Relevance Over 2.5 years, more than 950 000 US clinicians submitted greater than 270 million queries to an AI-enabled clinical information platform. Use varied across clinician types, specialties, and career stages and was frequently for treatment decisions rather than diagnostic tasks.