Ghaffari Faezeh, Langarizadeh Mostafa, Nabovati Ehsan, Sabery Mahdieh
Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
Health Information Management Research Center, Kashan University of Medical Sciences, Kashan, Iran.
Arch Acad Emerg Med. 2025 May 24;13(1):e49. doi: 10.22037/aaemj.v13i1.2690. eCollection 2025.
A growing area is the use of ChatGPT in simulation-based learning, a widely recognized methodology in medical education. This study aimed to evaluate ChatGPT's ability to generate realistic simulation scenarios to assist faculty as a significant challenge in medical education.
This study employs a qualitative research design and thematic analysis to interpret expert opinions The study was conducted in two phases. Scenario generation via ChatGPT and expert review for validation. We used ChatGPT (GPT-4) to create clinical scenarios on cardiovascular topics, including cardiogenic shock, postoperative cardiac tamponade after heart surgery, and heart failure. A panel of five experts, four nurses with expertise in emergency medicine and critical care and an anesthesia specialist, evaluated the scenarios. The experts' feedback, strengths and weaknesses, and proposed revisions from the expert discussions were analyzed via thematic analysis. Key themes and proposed revisions were identified, recorded, and compiled by the research team.
The clinical scenarios were produced by ChatGPT in less than 5 seconds per case. The thematic analysis identified six recurring themes in the experts' discussions: clinical accuracy, the clarity of learning objectives, the logical flow of patient cases, realism and feasibility, alignment with nursing competencies, and level of difficulty. All the experts agreed that the scenarios were realistic and followed clinical guidelines. However, they also identified several errors and areas that needed improvement. The experts identified and documented specific errors, incorrect recommendations, missing information, and inconsistencies with standard nursing practices.
It seems that, ChatGPT can be a valuable tool for developing clinical scenarios, but expert review and refinement are necessary to ensure the accuracy and alignment of the generated scenarios with clinical and educational standards.
一个不断发展的领域是ChatGPT在基于模拟的学习中的应用，这是医学教育中一种广泛认可的方法。本研究旨在评估ChatGPT生成逼真模拟场景以协助教师的能力，这是医学教育中的一项重大挑战。
本研究采用定性研究设计和主题分析来解读专家意见。该研究分两个阶段进行。通过ChatGPT生成场景并由专家进行验证审查。我们使用ChatGPT（GPT-4）创建关于心血管主题的临床场景，包括心源性休克、心脏手术后的术后心脏压塞和心力衰竭。由五名专家组成的小组，四名具有急诊医学和重症监护专业知识的护士以及一名麻醉专家，对这些场景进行了评估。通过主题分析对专家的反馈、优点和缺点以及专家讨论中提出的修订建议进行了分析。研究团队确定、记录并整理了关键主题和建议的修订内容。
ChatGPT生成每个临床场景的时间不到5秒。主题分析在专家讨论中确定了六个反复出现的主题：临床准确性、学习目标的清晰度、患者病例的逻辑流程、现实性和可行性、与护理能力的一致性以及难度水平。所有专家都认为这些场景是现实的且符合临床指南。然而，他们也发现了一些错误和需要改进的地方。专家们识别并记录了具体的错误、不正确的建议、缺失的信息以及与标准护理实践的不一致之处。
ChatGPT似乎可以成为开发临床场景的有价值工具，但需要专家审查和完善以确保生成的场景与临床和教育标准的准确性和一致性。
