Ambient AI Documentation: What the Research Actually Shows
Software that listens to the visit and drafts the note. The most widely bought healthcare AI right now, and the one with the fastest growing research base.
Ambient documentation is the rare healthcare AI that clinicians ask for rather than have imposed on them, which tells you how bad the paperwork got.
The pitch is simple. The software listens to the consultation, drafts the note, and the clinician edits and signs. The hoped-for result is a doctor who finishes the day without two hours of typing waiting at home.
Read this literature carefully, because most of it measures how clinicians feel rather than what changed. Satisfaction and burnout scores are real findings and they are not the same as minutes saved or patients seen. The studies that measured time are the interesting ones, and there are fewer of them.
What Kind of Evidence This Is
Not every study carries the same weight. This is the mix behind the list below.
What to Measure in Your Own Setting
A published result is somebody else's hospital. These are the numbers worth tracking in yours.
- Minutes spent in the record after hours, per clinician, before and after. This is the number the whole business case rests on.
- How much of the draft gets edited. A note that needs heavy rewriting has moved work rather than removed it.
- Clinician retention in the departments that adopted it first, because burnout is the outcome most of these deployments are really buying.
- Whether visit volume changed, and whether anybody intended it to. Time freed up gets filled, and who decides how is a management question rather than a software one.
The Studies
Every entry links to the source record. Summaries are the study's own abstract, shortened but not reworded.
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Ambient artificial intelligence scribes: physician burnout and perspectives on usability and documentation burden.
ObjectiveThis 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 methodsThis prospective quality improvement study was conducted at Stanford Health Care with 48 physicians over a 3-month period.
PMID 39657021 ... doi:10.1093/jamia/ocae295
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Clinician Experiences With Ambient Scribe Technology to Assist With Documentation Burden and Efficiency.
ImportanceTimely evaluation of ambient scribing technology is warranted to assess whether this technology can lessen the burden of clinical documentation on clinicians.ObjectiveTo investigate the association of ambient scribing technology with efficiency, quality, and perceived burden of clinical documentation in the outpatient setting.Design, setting, and participantsThis prospective, single-group pre-post quality i...
PMID 39969880 ... doi:10.1001/jamanetworkopen.2024.60637
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Ambient artificial intelligence scribes: utilization and impact on documentation time.
ObjectivesTo quantify utilization and impact on documentation time of a large language model-powered ambient artificial intelligence (AI) scribe.Materials and methodsThis prospective quality improvement study was conducted at a large academic medical center with 45 physicians from 8 ambulatory disciplines over 3 months.
PMID 39688515 ... doi:10.1093/jamia/ocae304
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The impact of nuance DAX ambient listening AI documentation: a cohort study.
ObjectiveTo assess the impact of the use of an ambient listening/digital scribing solution (Nuance Dragon Ambient eXperience (DAX)) on caregiver engagement, time spent on Electronic Health Record (EHR) including time after hours, productivity, attributed panel size for value-based care providers, documentation timeliness, and Current Procedural Terminology (CPT) submissions.Materials and methodsWe performed a peer-ma...
PMID 38345343 ... doi:10.1093/jamia/ocae022
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Physician Perspectives on Ambient AI Scribes.
ImportanceLimited qualitative studies exist evaluating ambient artificial intelligence (AI) scribe tools. Such studies can provide deeper insights into ambient AI implementations by capturing lived experiences.ObjectiveTo evaluate physician perspectives on ambient AI scribes.Design, setting, and participantsA qualitative study using semistructured interviews guided by the Reach, Efficacy, Adoption, Implementation, Ma...
PMID 40126477 ... doi:10.1001/jamanetworkopen.2025.1904
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Challenges of developing a digital scribe to reduce clinical documentation burden.
Clinicians spend a large amount of time on clinical documentation of patient encounters, often impacting quality of care and clinician satisfaction, and causing physician burnout. Advances in artificial intelligence (AI) and machine learning (ML) open the possibility of automating clinical documentation with digital scribes, using speech recognition to eliminate manual documentation by clinicians or medical scribes.
PMID 31799422 ... doi:10.1038/s41746-019-0190-1
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The digital scribe.
Current generation electronic health records suffer a number of problems that make them inefficient and associated with poor clinical satisfaction. Digital scribes or intelligent documentation support systems, take advantage of advances in speech recognition, natural language processing and artificial intelligence, to automate the clinical documentation task currently conducted by humans.
PMID 31304337 ... doi:10.1038/s41746-018-0066-9
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Evaluation of an Ambient Artificial Intelligence Documentation Platform for Clinicians.
ImportanceThe increase of electronic health record (EHR) work negatively impacts clinician well-being. One potential solution is incorporating an ambient artificial intelligence (AI) documentation platform.ObjectiveTo understand clinician experience before and after implementing ambient AI.Design, setting, and participantsThis quality improvement study was a pilot evaluation with before and after survey and EHR metri...
PMID 40314951 ... doi:10.1001/jamanetworkopen.2025.8614
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Use of an ambient artificial intelligence tool to improve quality of clinical documentation.
BackgroundElectronic health records (EHRs) have contributed to increased workloads for clinicians. Ambient artificial intelligence (AI) tools offer potential solutions, aiming to streamline clinical documentation and alleviate cognitive strain on healthcare providers.ObjectiveTo assess the clinical utility of an ambient AI tool in enhancing consultation experience and the completion of clinical documentation.MethodsO...
PMID 39371531 ... doi:10.1016/j.fhj.2024.100157
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Use of Ambient AI Scribes to Reduce Administrative Burden and Professional Burnout.
ImportanceWhile in short supply and high demand, ambulatory care clinicians spend more time on administrative tasks and documentation in the electronic health record than on direct patient care, which has been associated with burnout, intention to leave, and reduced quality of care.ObjectiveTo examine whether ambient AI scribes are associated with reducing clinician administrative burden and burnout.Design, setting, ...
PMID 41037268 ... doi:10.1001/jamanetworkopen.2025.34976
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Enhancing clinical documentation with ambient artificial intelligence: a quality improvement survey assessing clinician perspectives on work burden, burnout, and job satisfaction.
ObjectiveThis study evaluates the impact of an ambient artificial intelligence (AI) documentation platform on clinicians' perceptions of documentation workflow.Materials and methodsAn anonymous pre- and non-anonymous post-implementation survey evaluated ambulatory clinician perceptions on impact of Abridge, an ambient AI documentation platform.
PMID 39991073 ... doi:10.1093/jamiaopen/ooaf013
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Ambient AI Scribes in Clinical Practice: A Randomized Trial.
BackgroundAmbient artificial intelligence (AI) scribes record patient encounters and rapidly generate visit notes, representing a promising solution to documentation burden and physician burnout. However, the scribes' impacts have not been examined in randomized clinical trials.MethodsIn this parallel three-group pragmatic randomized clinical trial, 238 outpatient physicians, representing 14 specialties, were assigne...
PMID 41497288 ... doi:10.1056/aioa2501000
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Artificial Intelligence Scribe and Large Language Model Technology in Healthcare Documentation: Advantages, Limitations, and Recommendations.
Artificial intelligence (AI) scribe applications in the healthcare community are in the early adoption phase and offer unprecedented efficiency for medical documentation. They typically use an application programming interface with a large language model (LLM), for example, generative pretrained transformer 4.
PMID 39823022 ... doi:10.1097/gox.0000000000006450
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The association between use of ambient voice technology documentation during primary care patient encounters, documentation burden, and provider burnout.
BackgroundThe burden of documentation in the electronic medical record has been cited as a major factor in provider burnout. The aim of this study was to evaluate the association between ambient voice technology, coupled with natural language processing and artificial intelligence (DAX™), on primary care provider documentation burden and burnout.MethodsAn observational study of 110 primary care providers within a com...
PMID 37672297 ... doi:10.1093/fampra/cmad092
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The Impact of AI Scribes on Streamlining Clinical Documentation: A Systematic Review.
Background: Burnout among clinicians, including physicians, is a growing concern in healthcare. An overwhelming burden of clinical documentation is a significant contributor. While medical scribes have been employed to mitigate this burden, they have limitations such as cost, training needs, and high turnover rates.
PMID 40565474 ... doi:10.3390/healthcare13121447
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Ambient Documentation Technology in Clinician Experience of Documentation Burden and Burnout.
ImportanceDocumentation burden is associated with clinician burnout. To address documentation burden, Mass General Brigham (MGB) in Somerville, Massachusetts, and Emory Healthcare in Atlanta, Georgia, have piloted ambient documentation technology (ADT), which develops artificial intelligence-drafted clinical notes from clinician-patient conversations.ObjectiveTo examine the prevalence of ADT use and its association w...
PMID 40839265 ... doi:10.1001/jamanetworkopen.2025.28056
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Impact of an Artificial Intelligence-Based Solution on Clinicians' Clinical Documentation Experience: Initial Findings Using Ambient Listening Technology.
PMID 38980463 ... doi:10.1007/s11606-024-08924-2
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Artificial intelligence-driven digital scribes in clinical documentation: Pilot study assessing the impact on dermatologist workflow and patient encounters.
PMID 38571698 ... doi:10.1016/j.jdin.2024.02.009
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Clinical Implementation of Artificial Intelligence Scribes in Health Care: A Systematic Review.
Artificial intelligence (AI) scribes use advanced speech recognition and natural language processing to automate clinical documentation and ease administrative burden. However, little is known about the effect of AI scribes on clinicians, patients, and organizations.This study aimed to (1) propose an evaluation framework to guide future AI scribe implementations, (2) describe the effect of AI scribes along the domain...
PMID 40306686 ... doi:10.1055/a-2597-2017
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The Effect of Ambient Artificial Intelligence Notes on Provider Burnout.
BackgroundHealthcare provider burnout is a critical issue with significant implications for individual well-being, patient care, and healthcare system efficiency. Addressing burnout is essential for improving both provider well-being and the quality of patient care.
PMID 39500346 ... doi:10.1055/a-2461-4576
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AI Scribes in Health Care: Balancing Transformative Potential With Responsible Integration.
UnlabelledThe administrative burden of clinical documentation contributes to health care practitioner burnout and diverts valuable time away from direct patient care. Ambient artificial intelligence (AI) scribes-also called "digital scribes" or "AI scribes"-are emerging as a promising solution, given their potential to automate clinical note generation and reduce clinician workload, and those specifically built on a ...
PMID 40749188 ... doi:10.2196/80898
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Evaluating the Usability, Technical Performance, and Accuracy of Artificial Intelligence Scribes for Primary Care: Competitive Analysis.
BackgroundPrimary care providers (PCPs) face significant burnout due to increasing administrative and documentation demands, contributing to job dissatisfaction and impacting care quality. Artificial intelligence (AI) scribes have emerged as potential solutions to reduce administrative burden by automating clinical documentation of patient encounters.
PMID 40700466 ... doi:10.2196/71434
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A Pragmatic Randomized Controlled Trial of Ambient Artificial Intelligence to Improve Health Practitioner Well-Being.
BackgroundElectronic health record (EHR) documentation is a major contributor to work-related practitioner exhaustion and the interpersonal disengagement known as burnout. Generative artificial intelligence (AI) scribes that passively capture clinical conversations and draft visit notes may alleviate this burden, but evidence remains limited.MethodsA 24-week, stepped-wedge, individually randomized pragmatic trial was...
PMID 41625485 ... doi:10.1056/aioa2500945
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Assessing the quality of AI-generated clinical notes: validated evaluation of a large language model ambient scribe.
BackgroundGenerative artificial intelligence (AI) tools are increasingly being used as "ambient scribes" to generate drafts for clinical notes from patient encounters. Despite rapid adoption, few studies have systematically evaluated the quality of AI-generated documentation against physician standards using validated frameworks.ObjectiveThis study aimed to compare the quality of large language model (LLM)-generated ...
PMID 41199808 ... doi:10.3389/frai.2025.1691499
Study records come from Europe PMC, which indexes PubMed, MEDLINE, PMC and preprint servers. Titles, journals, years, identifiers, citation counts and abstracts are reproduced from the source record and are not rewritten here. Listing a study is not an endorsement of its conclusion, and citation count measures attention rather than quality. This page is a starting point for your own reading, not clinical guidance.