ArticleJAMIA open2024
Completeness and readability of GPT-4-generated multilingual discharge instructions in the pediatric emergency department.
Article in JAMIA open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- Artificial Intelligence-Mediated Discharge Document for Accessible Health Care (AIM-HEALTH): Protocol for a Prospective, Observational, Noninterventional Study.JMIR research protocols · 2026Observational
- Informing the Development of a High-Quality Emergency Department Discharge Process: Insights From Patients and Practitioners.The Permanente journal · 2026Article
- Patient Perceptions of Artificial Intelligence in Orthopaedic Surgery: Identifying Potential Barriers to Acceptance and Disparities With Implementation.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2026Article
- Dermatology "AI Babylon": Cross-Language Evaluation of AI-Crafted Dermatology Descriptions.Medicina (Kaunas, Lithuania) · 2026Article
- Effectiveness of large language models in preoperative and discharge education: a systematic review based on an evaluation framework.NPJ digital medicine · 2026Article
- Large language models in emergency medicine education: opportunities, challenges, and implementation pathways.Frontiers in public health · 2026Review
- Generative artificial intelligence in medicine.Nature medicine · 2025Review
- Tailored Education: Helping Every Student Across the Finish Line.Medical science educator · 2025Article
- Caregiver and Pediatric Clinician Perspectives on Artificial Intelligence for Language Services.Academic pediatricsArticle
- ChatGPT and human dietitian responses to diet-related questions on an online Q&A platform: A comparative study.Digital healthArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: The aim of this study was to assess the completeness and readability of generative pre-trained transformer-4 (GPT-4)-generated discharge instructions at prespecified reading levels for common pediatric emergency room complaints. Materials and Methods: The outputs for 6 discharge scenarios stratified by reading level (fifth or eighth grade) and language (English, Spanish) were generated fivefold using GPT-4. Specifically, 120 discharge instructions were produced and analyzed (6 scenarios: 60 in English, 60 in Spanish; 60 at a fifth-grade reading level, 60 at an eighth-grade reading level) and compared for completeness and readability (between language, between reading level, and stratified by group and reading level). Completeness was defined as the proportion of literature-derived key points included in discharge instructions. Readability was quantified using Flesch-Kincaid (English) and Fernandez-Huerta (Spanish) readability scores. Results: English-language GPT-generated discharge instructions contained a significantly higher proportion of must-include discharge instructions than those in Spanish (English: mean (standard error of the mean) = 62% (3%), Spanish: 53% (3%), Discussion: GPT-4 produced readable discharge instructions in English and Spanish while modulating document reading level. Discharge instructions in English tended to have higher completeness than those in Spanish. Conclusion: Future research in prompt engineering and GPT-4 performance, both generally and in multiple languages, is needed to reduce potential for health disparities by language and reading level.
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