ArticleNPJ digital medicine2024
Bridging the literacy gap for surgical consents: an AI-human expert collaborative approach.
Article in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 39 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
39 citing papers in PubMed.
- Communicating Drug Safety and Safe Use Conditions in Risk Evaluation and Mitigation Strategy Materials.Drug safety · 2026Article
- The Use of Artificial Intelligence to Improve Readability and Quality of Informed Consent Forms in Plastic and Reconstructive Surgery.Archives of plastic surgery · 2026Article
- Evaluating the ability of AI chatbots to provide informed consent information for common oncological surgeries.Annals of the Royal College of Surgeons of England · 2026Article
- Article
- Article
- Comprehensive Evaluation of AI Consent Forms in Otolaryngologic Surgery.World journal of otorhinolaryngology - head and neck surgery · 2026Article
- Patient-friendly simplification and translation of neuroradiology impressions using artificial intelligence.Scientific reports · 2026Article
- RESPECT: a conversational AI system for informed consent with accuracy, safety, and stakeholder-centered evaluation.NPJ digital medicine · 2026Article
- Article
- Optimization of University Counseling Consent Forms With Large Language Models: Multidimensional Comparative Evaluation.Journal of medical Internet research · 2026Article
- Evaluating large language models for simplifying non-English medical consent with clinician involvement.NPJ digital medicine · 2026Article
- Applications of Large Language Models in Medical Research: From Systematic Reviews to Clinical Studies.Bioengineering (Basel, Switzerland) · 2026Review
- A Survey on Medical Competence Evaluation Benchmarks for Large Language Models.Health care science · 2026Review
- Large language models for surgical informed consent: an ethical perspective on simulated empathy.Journal of medical ethics · 2026Article
- Can LLMs simplify operative notes? A comparative analysis in otorhinolaryngology.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Article
- Artificial Intelligence Techniques and Health Literacy: A Systematic Review.Mayo Clinic proceedings. Digital health · 2025Review
- Medical Consent in Cardiovascular Care: Time for Disruption?JACC. Advances · 2025Article
- Artificial Intelligence in Ambulatory Surgery: Current Applications, Challenges, and Future Directions.Journal of medical systems · 2025Review
- Large language models in clinical trials: applications, technical advances, and future directions.BMC medicine · 2025Review
- Better understanding: can a large language model safely improve readability of patient information leaflets in interventional radiology?BMJ health & care informatics · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the importance of informed consent in healthcare, the readability and specificity of consent forms often impede patients' comprehension. This study investigates the use of GPT-4 to simplify surgical consent forms and introduces an AI-human expert collaborative approach to validate content appropriateness. Consent forms from multiple institutions were assessed for readability and simplified using GPT-4, with pre- and post-simplification readability metrics compared using nonparametric tests. Independent reviews by medical authors and a malpractice defense attorney were conducted. Finally, GPT-4's potential for generating de novo procedure-specific consent forms was assessed, with forms evaluated using a validated 8-item rubric and expert subspecialty surgeon review. Analysis of 15 academic medical centers' consent forms revealed significant reductions in average reading time, word rarity, and passive sentence frequency (all P < 0.05) following GPT-4-faciliated simplification. Readability improved from an average college freshman to an 8th-grade level (P = 0.004), matching the average American's reading level. Medical and legal sufficiency consistency was confirmed. GPT-4 generated procedure-specific consent forms for five varied surgical procedures at an average 6th-grade reading level. These forms received perfect scores on a standardized consent form rubric and withstood scrutiny upon expert subspeciality surgeon review. This study demonstrates the first AI-human expert collaboration to enhance surgical consent forms, significantly improving readability without sacrificing clinical detail. Our framework could be extended to other patient communication materials, emphasizing clear communication and mitigating disparities related to health literacy barriers.
Identifiers
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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.