ArticleCureus2023
When Precision Meets Penmanship: ChatGPT and Surgery Documentation.
Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 3 of them syntheses 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
7 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Artificial Intelligence (AI) - Powered Documentation Systems in Healthcare: A Systematic Review.Journal of medical systems · 2025Pooled it
- Applications and Concerns of ChatGPT and Other Conversational Large Language Models in Health Care: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Artificial Intelligence and ChatGPT in Abdominopelvic Surgery: A Systematic Review of Applications and Impact.In vivo (Athens, Greece)Pooled it
- Mapping applications and evaluations of LLM-enabled AI chatbots for health purposes: a scoping review.Frontiers in public health · 2026Article
- Article
- A Systematic Review of ChatGPT and Other Conversational Large Language Models in Healthcare.medRxiv : the preprint server for health sciences · 2024Article
- Evaluating ChatGPT's accuracy in predicting postoperative nausea and vomiting risk and antiemetic prophylaxis planning: A study on simulated patient profiles.Saudi journal of anaesthesiaArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
ChatGPT (Chatbot Generative Pre-Trained Transformer) is an artificial intelligence with several potential applications in the field of medicine. As a large language model, it is particularly good at generating text. This study investigates the use of ChatGPT in constructing operation notes for laparoscopic appendicectomy, one of the most common surgical procedures in the UK. We prompted ChatGPT-4, the latest generation of ChatGPT, to produce operation notes for laparoscopic appendicectomy, which were then evaluated against 'Getting It Right First Time' (GIRFT) recommendations. GIRFT is an organisation that has collaborated with the National Health Service (NHS) to improve surgical documentation guidelines. Excluding certain items documented elsewhere in patient records, the generated notes were assessed against 30 key points in GIRFT recommendations. This process was repeated three times to obtain an average score. Our results showed that ChatGPT generated operation notes in seconds, with an average coverage of 78.8% (23.66 out of 30 points) of the GIRFT guidelines, surpassing average compliance with similar guidelines from the Royal College of Surgeons (RCS). However, the quality of ChatGPT's output was found to be dependent on the quality of the prompt, highlighting the need for verification of the generated content. Additionally, secure integration with electronic health records is required before ChatGPT can be adopted into the NHS.
Indexed as
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.