ArticlePlastic and reconstructive surgery. Global open2025
Artificial Intelligence Scribe and Large Language Model Technology in Healthcare Documentation: Advantages, Limitations, and Recommendations.
Article in Plastic and reconstructive surgery. Global open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
44 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Clinical Implementation of Artificial Intelligence Scribes in Health Care: A Systematic Review.Applied clinical informatics · 2025Pooled it
- Where is the patient in the records? Evaluating physiotherapists' first visit in occupational health primary care pathway for low back pain.BMJ open quality · 2026Trial
- Misaligned by design: evaluating and deploying generative AI for the real-world conditions of primary care: a Nordic and European perspective.Scandinavian journal of primary health care · 2026Article
- Exploring AI scribes in Norwegian general practice: a qualitative individual interview study.Scandinavian journal of primary health care · 2026Article
- Ambient Artificial Intelligence Scribes: A Scoping Review With Implications for Otolaryngology.The Laryngoscope · 2026Article
- The Use of Ambient Dictation Artificial Intelligence in Clinical Spaces in Surgery: A Scoping Review.World journal of otorhinolaryngology - head and neck surgery · 2026Review
- Novelty to necessity: large language models in clinical practice-a call to action for physicians.Internal and emergency medicine · 2026Review
- Large language models and artificial intelligence for generating, simplifying, and enhancing outpatient clinic letters: A systematic review.PLOS digital health · 2026Article
- "No BLT": The Rise and Risk of Acronyms in the Medical Record.HEC forum : an interdisciplinary journal on hospitals' ethical and legal issues · 2026Article
- Artificial Intelligence Scribes in Orthopaedic Surgery: A Narrative Review.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2026Review
- Exploring the Role of Large Language Models in Primary Care: Qualitative Study of Physicians in the United States and the Netherlands.JMIR medical informatics · 2026Article
- Feasibility of Tailoring Artificial Intelligence-Assisted Ambient Scribes for Intensive Care Unit Rounds: Algorithm Development and Validation.JMIR medical informatics · 2026Article
- Artificial Intelligence in Physical Therapy: A Narrative Review of Artificial Intelligence Applications Across the Patient and Client Management Model.Health science reports · 2026Article
- Charting Tomorrow: A Practical Review of Artificial Intelligence in Medical Documentation.Plastic and reconstructive surgery. Global open · 2026Article
- Large language models for post-discharge follow-up in erectile dysfunction care: a narrative review.Translational andrology and urology · 2026Review
- Automatic Speech Recognition in Healthcare in the Post-LLM Era: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- Framework for artificial intelligence implementation research in healthcare: synthesizing current evidence on barriers and facilitators.NPJ digital medicine · 2026Article
- AI-generated clinical summaries: errors and susceptibility to speech and speaker variability.BMJ health & care informatics · 2026Article
- Quality of Clinical Notes Created by Ambient Listening Generative AI: Pragmatic Prospective Pilot Study.JMIR medical informatics · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) scribe applications in the healthcare community are in the early adoption phase and offer unprecedented efficiency for medical documentation. They typically use an application programming interface with a large language model (LLM), for example, generative pretrained transformer 4. They use automatic speech recognition on the physician-patient interaction, generating a full medical note for the encounter, together with a draft follow-up e-mail for the patient and, often, recommendations, all within seconds or minutes. This provides physicians with increased cognitive freedom during medical encounters due to less time needed interfacing with electronic medical records. However, careful proofreading of the AI-generated language by the physician signing the note is essential. Insidious and potentially significant errors of omission, fabrication, or substitution may occur. The neural network algorithms of LLMs have unpredictable sensitivity to user input and inherent variability in their output. LLMs are unconstrained by established medical knowledge or rules. As they gain increasing levels of access to large corpora of medical records, the explosion of discovered knowledge comes with large potential risks, including to patient privacy, and potential bias in algorithms. Medical AI developers should use robust regulatory oversights, adhere to ethical guidelines, correct bias in algorithms, and improve detection and correction of deviations from the intended output.
Identifiers
What OpenQuestion holds
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.