ArticleJournal of the American Medical Informatics Association : JAMIA2026
Interviews with clinicians about an ambient artificial intelligence documentation platform.
Article in Journal of the American Medical Informatics Association : JAMIA, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evidence on artificial intelligence-assisted clinical documentation and healthcare workers' emotional wellbeing at work: a scoping review.Frontiers in psychology · 2026Pooled it
- Avoiding "shiny objects" and heeding "red flags": a sensemaking framework for emerging technology procurement.JAMIA open · 2026Article
- Hospital Human Resource Managers' Perspectives on Organizational Readiness for Generative AI Skills: Qualitative Descriptive Study.JMIR medical informatics · 2026Article
- Psychiatrists' experiences and opinions of generative AI: An exploratory online mixed methods survey in Germany.Digital healthArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveUnderstand the qualitative impact of an ambient artificial intelligence (AI) documentation platform on clinicians' experiences and workflows. MATERIALS AND
methodsA quality improvement (QI) qualitative study using semi-structured interviews after pilot implementation of an ambient AI documentation platform at a large healthcare organization in Northern and Central California. Pragmatic thematic analysis was used to code and analyze the interviews.
results100 clinicians were invited and 42 (42%) participated in an interview. 23 (54.8%) were males and 28 (66.7%) in primary care. Many respondents noted that ambient AI had decreased their cognitive burden by eliminating the need to remember as many specific visit details and saved time for other tasks. They also liked how ambient AI generated transcripts in multiple languages and then created an English-language progress note. However, clinicians also reported challenges, particularly missed or inaccurate information that required them to review the transcript/audio and edit the note. Additionally, many clinicians, particularly specialists, disliked the note formatting and the inability to customize the note template as this resulted in additional manual editing. DISCUSSION: Results from these QI qualitative interviews suggest that ambient AI improved clinicians' overall experience at work.
conclusionWhile there are many similarities, there may be key differences in clinician experience between ambient AI documentation platforms depending on unique features of each. Future research is needed to understand the potential range of experiences based on type of ambient AI platform and if these findings continue with longer use and broader expansion of this new and evolving technology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.