ArticleJournal of hand surgery global online2026
Eliminating Nonvalue-Added Tasks in Health Care: Artificial Intelligence in the Orthopedic Office.
Article in Journal of hand surgery global online, 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.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: This study examines the efficiency and proof-of-concept use of a generative artificial intelligence (AI) documentation prototype, evaluating whether it can produce usable notes and estimating its potential time advantage compared with physician-produced documentation in an orthopedic practice. Methods: A comparative study analyzed AI-generated documentation versus physician-generated documentation of 68 new patient encounters with a board-certified hand surgeon, including surgical and nonsurgical patients presenting for evaluation of upper-extremity conditions. AI-generated documentation was created using unedited audiorecordings of encounters containing no identifiable patient information that were processed by standardized ChatGPT prompts. A senior resident (PGY-5) categorized all visits as minimal, low, or moderate complexity using the Centers for Medicare & Medicaid Services guidelines. Variables measured were documentation time (AI and physician), and physician time to edit AI documentation, visit complexity, visit time of day, patient demographics, and a physician-produced note quality assessment using a 5-point Likert scale. Results: Editing AI-generated documentation required a median of 55.1 seconds, compared with 81.2 seconds for physician-generated documentation. AI-generated notes were generally high quality, with 91% rated 4 or 5 on a 5-point Likert scale. Physician documentation time increased with greater visit complexity, whereas AI-documentation time showed minimal variation across complexity levels; complexity-stratified findings should be interpreted as exploratory because of sample size. Critical errors resulting in incomprehensible or erroneous content were identified in six (8.8%) AI-generated documents. Conclusions: This proof-of-concept study demonstrates that AI can produce clinically usable notes across varying encounter complexities and that physician editing of AI-generated documentation is faster than independent documentation. Although human oversight remains essential, AI-assisted documentation has substantial potential to improve workflow efficiency. Level of evidence: IV.
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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.