ArticleJMIR medical informatics2025
Clinical Performance and Communication Skills of ChatGPT Versus Physicians in Emergency Medicine: Simulated Patient Study.
Article in JMIR medical informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Evaluating and Validating Large Language Models for Health Education on Developmental Dysplasia of the Hip: 2-Phase Study With Expert Ratings and a Pilot Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- Comparing the text-based diagnostic reasoning performance of emergency medicine physicians and large language models in both definitive and differential diagnoses using standardized clinical vignettes: a preliminary study.International journal of emergency medicine · 2026Article
- Rapid Development and Testing of Behavioral Text Message Reminders for Antidepressant Adherence via Online Panels: Survey Study.Journal of medical Internet research · 2026Article
- Applications, Challenges, and Future Directions of Large Language Models in Health Care Communication: Scoping Review.Journal of medical Internet research · 2026Article
- Training Empathetic Communication Skills in Medical Students With a Role-Prompted GPT-4o Chatbot: Quasi-Experimental Intervention Study.JMIR medical education · 2026Article
- The risk of empty empathy talk and challenges of automated empathy in healthcare communication.NPJ digital medicine · 2026Review
- Safety-First Framework for AI-Enabled Anamnesis in Head and Neck Surgery: Evidence Synthesis from a Narrative Review.Journal of clinical medicine · 2026Review
- Identification of quality and safety concerns in AI chatbot responses to procedural sedation: a comparative evaluation of ChatGPT, Gemini, and Copilot.Frontiers in health services · 2026Article
- Author's Reply: "Data Contamination in AI Evaluation".JMIR medical informatics · 2025Article
- Data Contamination in AI Evaluation.JMIR medical informatics · 2025Article
- Comparative evaluation of artificial intelligence chatbots for real-time guidance during intraoperative anesthetic crises: A simulation-based study.Saudi journal of anaesthesiaArticle
- Comparing Artificial intelligence to physicians' competences in the domain of clinical reasoning: A systematic review and meta-analysis.Journal of medical education and curricular developmentReview
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Authors and funding
5 authors.
Funding
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Abstract
Background: Emergency medicine can benefit from artificial intelligence (AI) due to its unique challenges, such as high patient volume and the need for urgent interventions. However, it remains difficult to assess the applicability of AI systems to real-world emergency medicine practice, which requires not only medical knowledge but also adaptable problem-solving and effective communication skills. Objective: We aimed to evaluate ChatGPT's (OpenAI) performance in comparison to human doctors in simulated emergency medicine settings, using the framework of clinical performance examination and written examinations. Methods: In total, 12 human doctors were recruited to represent the medical professionals. Both ChatGPT and the human doctors were instructed to manage each case like real clinical settings with 12 simulated patients. After the clinical performance examination sessions, the conversation records were evaluated by an emergency medicine professor on history taking, clinical accuracy, and empathy on a 5-point Likert scale. Simulated patients completed a 5-point scale survey including overall comprehensibility, credibility, and concern reduction for each case. In addition, they evaluated whether the doctor they interacted with was similar to a human doctor. An additional evaluation was performed using vignette-based written examinations to assess diagnosis, investigation, and treatment planning. The mean scores from ChatGPT were then compared with those of the human doctors. Results: ChatGPT scored significantly higher than the physicians in both history-taking (mean score 3.91, SD 0.67 vs mean score 2.67, SD 0.78, P<.001) and empathy (mean score 4.50, SD 0.67 vs mean score 1.75, SD 0.62, P<.001). However, there was no significant difference in clinical accuracy. In the survey conducted with simulated patients, ChatGPT scored higher for concern reduction (mean score 4.33, SD 0.78 vs mean score 3.58, SD 0.90, P=.04). For comprehensibility and credibility, ChatGPT showed better performance, but the difference was not significant. In the similarity assessment score, no significant difference was observed (mean score 3.50, SD 1.78 vs mean score 3.25, SD 1.86, P=.71). Conclusions: ChatGPT's performance highlights its potential as a valuable adjunct in emergency medicine, demonstrating comparable proficiency in knowledge application, efficiency, and empathetic patient interaction. These results suggest that a collaborative health care model, integrating AI with human expertise, could enhance patient care and outcomes.
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