Back to search

Article

From Conversation to Chart: An Analysis of Clinician Edits to Ambient AI Draft Notes

2026-01-06

Abstract excerpt

<h4>Structured Abstract</h4> <h4>Objective</h4> Ambient artificial intelligence (AI) tools are increasingly adopted in clinical practices. This study investigated whether and how clinicians edit AI-generated drafts and the linguistic differences between AI drafts and clinician-finalized notes. <h4>Materials and Methods</h4> This retrospective study analyzed real-world data from ambulatory clinics at a large aca...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
ebbc00ec-c23c-5b2b-be5f-187fde84fc05
DOI
10.64898/2026.01.05.26343471
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
From Conversation to Chart: An Analysis of Clinician Edits to Ambient AI Draft NotesDOI 10.64898/2026.01.05.26343471
Clinicians’ Rationale for Editing Ambient AI–Drafted Clinical Notes: Persistent Challenges and Implications for ImprovementSemantic proximity
What Do Clinicians Edit in Ambient AI-Drafted Clinical Documentation? A Qualitative Content AnalysisSemantic proximity
Impact of an AI medical scribe after 375 000 notes generated across care levels in a European health systemSemantic proximity
Linguistic Effects of Ambient AI on Clinical Documentation: A Matched Pre-Post StudySemantic proximity
Understanding Clinician Edits to Ambient AI Draft Notes: A Feasibility Analysis Using Large Language ModelsSemantic proximity
A Novel Playbook for Pragmatic Trial Operations to Monitor and Evaluate Ambient Artificial Intelligence in Clinical PracticeSemantic proximity
Accuracy and Safety of an AI Ambient Scribe Compared with Handwritten Clinical NotesSemantic proximity
Quality, consistency, and clinical safety of AI-generated versus clinician-written clinical notes: a multi-country paired simulation studySemantic proximity
Benchmarking And Datasets For Ambient Clinical Documentation: A Scoping Review Of Existing Frameworks And Metrics For AI-Assisted Medical Note GenerationSemantic proximity
AI Notetaking in Psychotherapy: Consent, Efficiency, and Clinical Outcomes from a Large-Scale EvaluationSemantic proximity
An LLM-Based Comparison of Ambient AI Scribes for Clinical DocumentationSemantic proximity
Ambient AI Documentation in Mixed-Language Encounters: A Heuristic Evaluation of Reenacted Mandarin–English and Spanish–English Clinical ConversationsSemantic proximity
Select a neighboring publication to make it the new centre.