Observational studyApplied clinical informatics2026
The Effect of Ambient Artificial Intelligence Documentation on Clinician Workload, Efficiency, and Patient Experience in a Multisite Emergency Department Network.
Observational study in Applied clinical informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abstract:
backgroundAmbient artificial intelligence (AI) documentation systems have emerged as a potential solution to clerical burden in medicine, yet evidence in emergency settings remains limited. Abstract:
objectivesThe objective of this study is to evaluate the ambient AI on patient experience, documentation efficiency, clinician workload, and clinical throughput across a large emergency department (ED) network. Abstract:
methodsThis is a retrospective, observational cohort study of ambient AI rollout across 14 EDs (May 2024-June 2025). Clinicians applied the tool on a voluntary basis and contributed both AI-assisted and conventional notes. Outcomes included patient-reported experience, active editing time, disposition-to-completion time, copied-forward content, and on-time note completion. Clinician workload was assessed with pre- and postimplementation surveys including the NASA Task Load Index (TLX). Abstract:
resultsAmbient AI was used in 8.6% of 315,242 ED clinical notes. AI use was associated with higher top-box ratings for clinician listening (82.0 vs. 76.6%; odds ratio [OR]: 1.39; Abstract:
conclusionAmbient AI documentation was associated with improved patient-reported listening, earlier note completion, reduced copied-forward content, and lower clinician-perceived cognitive burden, without altering active editing time per note. These findings suggest a scalable tool for reducing clerical burden in high-throughput emergency care, while introducing new responsibilities for clinicians to review, edit, and sign machine-generated notes.
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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.