This paper is in the following e-collection/theme issue:

Chatbots and Conversational Agents (741) Natural Language Processing (917) Artificial Intelligence (2135) Generative Language Models Including ChatGPT (708) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (698) Methods and Instruments in Medical Informatics (190)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57721, first published .
Comparison of the Quality of Discharge Letters Written by Large Language Models and Junior Clinicians: Single-Blinded Study

Comparison of the Quality of Discharge Letters Written by Large Language Models and Junior Clinicians: Single-Blinded Study

Comparison of the Quality of Discharge Letters Written by Large Language Models and Junior Clinicians: Single-Blinded Study

Authors of this article:

Joshua Yi Min Tung1, 2 Author Orcid Image ;   Sunil Ravinder Gill1 Author Orcid Image ;   Gerald Gui Ren Sng2, 3 Author Orcid Image ;   Daniel Yan Zheng Lim2, 4 Author Orcid Image ;   Yuhe Ke2, 5 Author Orcid Image ;   Ting Fang Tan6 Author Orcid Image ;   Liyuan Jin7 Author Orcid Image ;   Kabilan Elangovan8 Author Orcid Image ;   Jasmine Chiat Ling Ong9 Author Orcid Image ;   Hairil Rizal Abdullah2, 5 Author Orcid Image ;   Daniel Shu Wei Ting6, 7, 8 Author Orcid Image ;   Tsung Wen Chong1 Author Orcid Image
Article Authors Cited by (21) Tweetations Metrics

Journals

  1. Schwieger A, Angst K, de Bardeci M, Burrer A, Cathomas F, Ferrea S, Grätz F, Knorr M, Kronenberg G, Spiller T, Troi D, Seifritz E, Weber S, Olbrich S. Large language models can support generation of standardized discharge summaries – A retrospective study utilizing ChatGPT-4 and electronic health records. International Journal of Medical Informatics 2024;192:105654 View
  2. Hou Y, Bert C, Gomaa A, Lahmer G, Höfler D, Weissmann T, Voigt R, Schubert P, Schmitter C, Depardon A, Semrau S, Maier A, Fietkau R, Huang Y, Putz F. Fine-tuning a local LLaMA-3 large language model for automated privacy-preserving physician letter generation in radiation oncology. Frontiers in Artificial Intelligence 2025;7 View
  3. Bracken A, Reilly C, Feeley A, Sheehan E, Merghani K, Feeley I. Artificial Intelligence (AI) – Powered Documentation Systems in Healthcare: A Systematic Review. Journal of Medical Systems 2025;49(1) View
  4. Ng I, Tung D, Seet T, Yow K, Chan K, Teo D, Chua C. How to write a good discharge summary: a primer for junior physicians. Postgraduate Medical Journal 2025;101(1198):764 View
  5. Ozdag Y, Mahmoud M, Klena J, Grandizio L. Artificial Intelligence in Personal Statements Within Orthopaedic Surgery Residency Applications. Journal of the American Academy of Orthopaedic Surgeons 2025;33(10):554 View
  6. Zhou J, Zhang J, Wan R, Cui X, Liu Q, Guo H, Shi X, Fu B, Meng J, Yue B, Zhang Y, Zhang Z. Integrating AI into clinical education: evaluating general practice trainees’ proficiency in distinguishing AI-generated hallucinations and impacting factors. BMC Medical Education 2025;25(1) View
  7. Li S, Jiang J, Yang X. Preliminary assessment of large language models’ performance in answering questions on developmental dysplasia of the hip. Journal of Children's Orthopaedics 2025;19(3):207 View
  8. Morgan D, Branch-Elliman W, Goodman K. Time to Study Implementation of AI-Generated Discharge Summaries. JAMA Internal Medicine 2025;185(7):825 View
  9. Idan D, Einav S. Primer on large language models: an educational overview for intensivists. Critical Care 2025;29(1) View
  10. Ng I, Choe R, Ong S, Thng C, Neo J, Teo D, Chua C. Postgraduate Pedagogical Training and Interventions to Promote High‐Quality Discharge Summaries. The Clinical Teacher 2025;22(5) View
  11. Li X, Zhang Y, Zheng T, Deng Y, Lu Y, Hu J, Chen S, Li Y, Wang K. Using large language models to generate child-friendly education materials on myopia. DIGITAL HEALTH 2025;11 View
  12. Small W, Austrian J, O’Donnell L, Burk-Rafel J, Hochman K, Goodman A, Zaretsky J, Martin J, Johnson S, Major V, Jones S, Henke C, Verplanke B, Osso J, Larson I, Saxena A, Mednick A, Simonis C, Han J, Kesari R, Wu X, Heery L, Desel T, Baskharoun S, Figman N, Farooq U, Shah K, Jahan N, Kim J, Testa P, Feldman J. Evaluating Hospital Course Summarization by an Electronic Health Record–Based Large Language Model. JAMA Network Open 2025;8(8):e2526339 View
  13. Kim H, Lee S, You S, Huh S, Kim J, Kim S, Ko D, Kim J, Lee J, Lim J, Park M, Lee K. A Bilingual On-Premises AI Agent for Clinical Drafting: Implementation Report of Seamless Electronic Health Records Integration in the Y-KNOT Project. JMIR Medical Informatics 2025;13:e76848 View
  14. Rabil M, Choksi A, Leapman M. Harmonizing environmental and economic forces in urologic care. Current Opinion in Urology 2025;35(6):679 View
  15. Mohamed A, Elasad A, Fuad U, Pengas I, Elsayed A, Bhamidipati P, Salib P. Artificial Intelligence in Trauma and Orthopaedic Surgery: A Comprehensive Review From Diagnosis to Rehabilitation. Cureus 2025 View
  16. Song J, Park J, Kim J, You S. Large Language Model Assistant for Emergency Department Discharge Documentation. JAMA Network Open 2025;8(10):e2538427 View
  17. Rattananan W. Completeness and Quality of Neurology Referral Letters Generated by a Large Language Model for Standardized Scenarios. Medicina 2025;61(11):1931 View
  18. Auerbach A, Weerahandi H. Patient Safety During Transitions. Medical Clinics of North America 2025 View
  19. Schroeder A, Tran Z, Sexton K, Salzberg A. Clinician’s Guide to Artificial Intelligence. Medical Clinics of North America 2025 View

Books/Policy Documents

  1. Paraschiv E, Elena Cîrnu C, Victor Vevera A. Electronic Health Records - Issues and Challenges in Healthcare Systems. View
  2. Taheri A, Farhadi A, Zamanifar A. Application of Generative AI in Healthcare Systems. View