ArticleAnnals of the Royal College of Surgeons of England2025
A quality improvement project of patient perception of AI-generated discharge summaries: a comparison with doctor-written summaries.
Article in Annals of the Royal College of Surgeons of England, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence (AI) and Healthcare Capabilities: A Systematic Review and Research Directions.F1000Research · 2025Pooled it
- Artificial intelligence in the emergency department-- applications, perceptions and limitations: a narrative review.World journal of emergency medicine · 2026Review
- Interdisciplinary Development and Fine-Tuning of CARDIO, a Large Language Model for Cardiovascular Health Education in HIV Care: Tutorial.Journal of medical Internet research · 2025Article
- Investigation of the Optimal Length of Discharge Summaries in Care Transitions: A Cross-sectional Study.Journal of community hospital internal medicine perspectives · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionEvery patient admitted to hospital should receive a discharge letter when they leave. Artificial intelligence (AI) has the capability to fulfil this task. Here, we investigate the use of AI to generate discharge letters compared with letters written by a doctor.
methodsUsing an AI tool, ChatGPT, we generated two discharge letters for hypothetical elective tonsillectomy patients. We asked the parents of paediatric tonsillectomy patients to blindly compare the AI letters with two anonymised real discharge letters for tonsillectomy patients, written by two ear, nose and throat (ENT) doctors. Participants were asked to rate the quality of medical information, the ease of reading and the length of each of the four discharge letters. They were also asked to deduce who they thought wrote each discharge letter (AI or a doctor).
resultsForty-seven parents responded to the survey. Our results demonstrate that the AI letters were reported to contain significantly better medical information (
conclusionsAI tools have the potential to write tonsillectomy discharge letters of comparable quality (as perceived by our participant population) to those written by ENT doctors. This study provides preliminary evidence to show that AI-generated discharge letters may be an interesting avenue of further investigation as an application for this tool.
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Registered trials
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