ArticleJAMA2026
Changes in Clinician Time Expenditure and Visit Quantity With Adoption of Artificial Intelligence-Powered Scribes: A Multisite Study.
Article in JAMA, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed.
- Well, How Did We Get Here? The Current State of Pediatric Endocrinology.Journal of pediatrics. Clinical practice · 2026Article
- Current Trends in AI and Eye Disease Diagnostics.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2026Review
- Navigating Collective Bargaining Barriers to the Implementation of AI Scribe Technology Among Ambulatory Advanced Practice Providers: Mixed Methods Quality Improvement Study.JMIR formative research · 2026Article
- Consensus framework for the validation of generative AI: call for collaborators on the Validation Accords.Nature medicine · 2026Article
- Evidence, use cases, and implementation safeguards of large language models in primary care.Communications medicine · 2026Review
- Please document the nature of the medical emergency.BMJ quality & safety · 2026Article
- Physician burnout in rheumatology: are medical scribes part of the solution?Clinical rheumatology · 2026Review
- Review
- Governing the attention dividend: AI-reclaimed clinician capacity as a health policy resource.Health affairs scholar · 2026Article
- Article
- Perspectives of Individuals With Obsessive-Compulsive Disorder on the Role of Artificial Intelligence in Therapy and Treatment: Thematic Qualitative Study.Journal of participatory medicine · 2026Article
- Digital Mental Health Research Priorities, Revisited for the AI and Large Language Model Era.JMIR mental health · 2026Article
- Selecting, Scaling, and Measuring the Value of Ambient AI in a Nonacademic Health System: Multiphase Pilot Study.JMIR medical informatics · 2026Article
- Hospitalists Are Already Using AI-Why Implementation Will Determine Its Impact.Journal of medical Internet research · 2026Article
- From Clinical Encounter to Draft Documentation: A Mechanistic Narrative Review of Ambient Scribe Technology.Cureus · 2026Review
- [Artificial intelligence in daily urological care: results of the AI barometer].Urologie (Heidelberg, Germany) · 2026Article
- Cognitive reshaping and resurgence of humanness: restructuring the medical education continuum in the era of generative AI.Frontiers in medicine · 2026Review
- Work outside of work: after-hours use of the electronic medical record among residents at an academic veterinary teaching hospital.Frontiers in veterinary science · 2026Article
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Authors and funding
31 authors.
Funding
Abstract
Importance: Artificial intelligence (AI)-enabled scribes have been proposed to reduce electronic health record (EHR) burden and improve clinician satisfaction. There is limited evidence about their associated results across multiple sites and relative benefits for different clinician groups. Objective: To assess the association of AI scribe adoption with changes in EHR time expenditure and visit volume and how associations vary by clinician characteristics. Design, Setting, and Participants: Multisite, longitudinal cohort study of AI scribe adoption conducted at 5 US academic health care institutions that introduced AI scribes to their clinicians between June 2023 and August 2025. Participants were ambulatory clinicians. Exposures: AI scribe adoption, defined as receiving access to an AI scribe. This was determined by opt-in decisions by eligible physicians at 4 of the 5 sites. Main Outcome and Measures: Total time spent on the EHR, time spent on documentation, and time spent on the EHR outside scheduled hours or on unscheduled days, all normalized to 8 scheduled patient hours; weekly visit volume. Results: The sample comprised 8581 clinicians, including 1809 AI scribe adopters. Participants were 57.1% female and were split between primary care (24.4%), medical (62.4%), and surgical (13.2%) specialties. Most (74.1%) were attending physicians, with 18.1% advanced practice clinicians and 7.8% resident physicians. In a difference-in-differences analysis, AI scribe adoption was associated with 13.4 (95% CI, 9.1-17.7) fewer minutes of EHR time, 16.0 (95% CI, 13.7-18.3) fewer minutes of documentation time, and 0.49 (95% CI, 0.17-0.81) additional weekly visits delivered. Electronic health record time outside work hours did not change significantly. Changes associated with AI scribe adoption were greatest for primary care specialists, advanced practice clinicians, female clinicians, and clinicians who used AI scribes in 50% or more of visits. Conclusions and Relevance: AI scribe adoption was associated with modest decreases in total EHR time and documentation time and with a modest increase in weekly visit volume.
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