Evidence map›Paper›PMID 42403728›Full record

ReviewCureus2026

From Clinical Encounter to Draft Documentation: A Mechanistic Narrative Review of Ambient Scribe Technology.

Thomas W Kuhn

Abstract readReview
In one paragraph

Review in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Thomas W KuhnBehavioral Health Services, Holland Hospital, Holland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinicians and health systems increasingly use ambient scribe tools to generate draft clinical notes in an effort to reduce documentation burden, enhance workflow, and improve clinician and patient experience. Safe and effective use is enhanced by understanding that the draft note is not a direct record of the encounter, but the product of a multistage representational process in which clinical sound is captured, converted into digital data, transformed into text, and reshaped into documentation. This narrative review examined literature from November 2025 through May 2026 using PubMed, IEEE Xplore, IsisCB Explore, ACM Digital Library, arXiv, Google Scholar, and citation tracking, prioritizing peer-reviewed sources with selective inclusion of foundational technical and conceptual works. The review translates a clinician-accessible account of the ambient scribe pipeline into practical guidance for clinician use. Privacy, consent, and medicolegal issues are also considered, including remote data transmission and clinician responsibility for the final note. This analysis leads to the 3C approach: Choose, Capture, Check. This framework emphasizes clinician decision-making before the encounter, deliberate communication and capture practices during the encounter, and targeted review after note generation.

Indexed as

ambient scribeartificial intelligence (ai) in medicineautomatic speech recognitionclinical documentationclinician workflowinformed consentlarge language modelsmedical informatics

Identifiers

PMID42403728
PMCPMC13331764

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.