Ambient artificial intelligence scribes: physician burnout and perspectives on usability and documentation burden.
Open accessAbstract
Objective: This study evaluates the pilot implementation of ambient AI scribe technology to assess physician perspectives on usability and the impact on physician burden and burnout. Materials and Methods: This prospective quality improvement study was conducted at Stanford Health Care with 48 physicians over a 3-month period. Outcome measures included burden, burnout, usability, and perceived time savings. Results: Paired survey analysis (n = 38) revealed large statistically significant reductions in task load (−24.42, p <.001) and burnout (−1.94, p <.001), and moderate statistically significant improvements in usability scores (+10.9, p <.001). Post-survey responses (n = 46) indicated favorable utility with improved perceptions of efficiency, documentation quality, and ease of use. Discussion: In one of the first pilot implementations of ambient AI scribe technology, improvements in physician task load, burnout, and usability were demonstrated. Conclusion: Ambient AI scribes like DAX Copilot may enhance clinical workflows. Further research is needed to optimize widespread implementation and evaluate long-term impacts.
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Ambient AI was associated with decreased cognitive load (mental demand, temporal demand, and effort).
“Overall, our pilot project found that ambient AI was associated with decreased cognitive load (mental demand, temporal demand, and effort) like Shah et al10 found”
From Evaluation of an Ambient Artificial Intelligence Documentation Platform for Clinicians (2025) · cites this paper as [10]
The Data collection and study measures section defines the physician task-load score as a measure of cognitive task load, and the Pre versus post survey results section reports a significant reduction after ambient AI scribe use. The paper reports an aggregate score, however, not separate decreases in mental demand, temporal demand, and effort. (LLM, conf=0.85)
Experimental — accuracy not yet measuredPrior work has explored the impact of ambient AI scribes on patient-provider interactions primarily in ambulatory settings.
“While prior work has explored the impact of this technology on patient-provider interactions primarily in ambulatory settings”
From Clinician Perspectives on Ambient AI Scribes in the Intensive Care Unit: Qualitative Interview Study (2026) · cites this paper as [11]
The Discussion describes a pilot involving primary-care and ambulatory-specialty physicians and mentions physician–patient engagement as a possible benefit. But the Objective and study measures focus on physician usability, documentation burden, and burnout; the paper does not evaluate the impact on patient–provider interactions. The ambulatory setting is supported, but the claimed focus on interactions is not. (LLM, conf=0.84)
Experimental — accuracy not yet measuredFully autonomous, EHR-integrated ambient AI scribes have been used primarily in the ambulatory outpatient setting, with improvements in physician task load, burnout, and usability.
“To date, fully autonomous, EHR-integrated scribes have been used primarily in the ambulatory outpatient setting, with improvements in physician task load, burnout, and usability [10-12].”
From Clinician Perspectives on Ambient AI Scribes in the Intensive Care Unit: Qualitative Interview Study (2026) · cites this paper as [11]
The Technology implementation and physician training section describes an EHR-integrated ambient scribe, and Pre versus post survey results reports improved task load, burnout, and usability among primary-care and ambulatory-specialty physicians. The paper does not establish that such scribes have been used primarily in outpatient settings overall. It also describes clinician review of generated notes, rather than establishing that the system is fully autonomous. The indexed passages provide section labels but no page numbers. (LLM, conf=0.85)
Experimental — accuracy not yet measuredAmbient AI was associated with a reduction in task load in initial survey results.
“a reduction in task load,10”
From Evaluation of an Ambient Artificial Intelligence Documentation Platform for Clinicians (2025) · cites this paper as [10]
Initial survey results showed significant improvements in self-reported documentation aspects after ambient AI.
“Initial survey results showed significant improvements in self-reported documentation aspects, such as a reduction in task load,10 ease of processes,8 improved clinician wellness (including overall well-being8 and decreased burnout), and a perceived impact on patient experience8 after ambient AI.”
From Evaluation of an Ambient Artificial Intelligence Documentation Platform for Clinicians (2025) · cites this paper as [10]
Ambient AI was associated with improved satisfaction at work.
“and with improved satisfaction at work, echoing previous research,10,15”
From Evaluation of an Ambient Artificial Intelligence Documentation Platform for Clinicians (2025) · cites this paper as [10]
The Pre versus post survey results report reduced physician work exhaustion and task load after the ambient AI scribe pilot. The Data collection and study measures section identifies burnout, burden, usability, and acceptability measures, but not satisfaction at work; a search for satisfaction found no study finding on that outcome. (LLM, conf=0.74)
Experimental — accuracy not yet measured
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- Authors
- Shah, S. J., Devon-Sand, A., Ma, S. P., Jeong, Y., Crowell, T., Smith, M., Liang, A. S., Delahaie, C., Hsia, C., Shanafelt, T., Pfeffer, M. A., Sharp, C., Lin, S., & Garcia, P.
- Affiliations
- Stanford Health Care (US)
- Stanford Medicine (US)
- Department of Medicine, Stanford University School of Medicine , Stanford, CA 94305,
- Corresponding author
- Shah, Shreya J
- ORCID
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2024-12-05
- Volume
- 32
- Issue
- 2
- Pages
- 375-380
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC11756571
- OpenAlex
- W4405225674
- Cited by
- 224
- References
- 27
- Citations by year
- 2026: 132 · 2025: 92
- FWCI
- 68.45
- Type
- journal article
- Language
- en
- Open access
- green
- pmc.ncbi.nlm.nih.gov
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › General Health Professions › Healthcare professionals’ stress and burnout
- Keywords
- ambient AI scribes, physician burnout, clinical documentation burden, usability, workload, clinical workflow, physician attitudes, time savings
- MeSH terms
- Artificial Intelligence, Attitude of Health Personnel, Burnout, Professional, Documentation, Female, Humans, Male, Physicians, Pilot Projects, Prospective Studies, Surveys and Questionnaires, User-Computer Interface, Workload, Workflow, Electronic Health Records, Quality Improvement
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