中华医学教育杂志

中华医学教育杂志 ›› 2025, Vol. 45 ›› Issue (11): 843-848.DOI: 10.3760/cma.j.cn115259-20250109-00023

• 教育技术 • 上一篇    下一篇

人工智能赋能临床医学专业实习生大病历书写培训的创新实践

茅凯凯, 李秀, 周晨, 张广, 林永娟, 赵晓智   

  1. 南京大学医学院附属鼓楼医院教育处,南京 210008
  • 收稿日期:2025-01-09 发布日期:2025-10-30
  • 通讯作者: 赵晓智, Email: zhaoxz@nju.edu.cn
  • 基金资助:
    2024年江苏省高等教育学会专项课题(2024JSGJ16);2025年江苏省高等教育教改研究课题(2025JGYB335)

Innovative practice of AI-empowered training for writing medical records of clinical interns

Mao Kaikai, Li Xiu, Zhou Chen, Zhang Guang, Lin Yongjuan, Zhao Xiaozhi   

  1. Department of Education, Nanjing Drum Tower Hospital Affiliated to Nanjing University Medical School, Nanjing 210008, China
  • Received:2025-01-09 Published:2025-10-30
  • Contact: Zhao Xiaozhi, Email: zhaoxz@nju.edu.cn
  • Supported by:
    Special Project of Jiangsu Higher Education Society (2024JSGJ16); Higher Education Teaching Reform Research Project in Jiangsu Province for 2025 (2025JGYB335)

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摘要： 目的 探讨基于人工智能的临床医学专业实习生大病历书写培训系统在提高实习生大病历书写质量和提升教学效率方面的应用效果。方法 选取2024—2025学年在南京大学医学院附属鼓楼医院实习的145名临床医学专业学生作为研究对象,以简单随机方法将其分为试验组(73名学生)和对照组(72名学生)。试验组学生应用人工智能大病历书写培训系统(简称培训系统)进行病历书写教学,对照组学生则实施传统教学方式。通过实习前后病历书写考核和满意度问卷调查评估不同教学方式的应用效果。采用独立样本t检验和描述性统计分析数据。结果 试验组学生病历考核后测总分为(85.73±6.44)分,高于对照组学生的(80.10±6.04)分,其差异具有统计学意义(P<0.001)。问卷调查结果显示,试验组61名(83.6%)学生认为培训系统提高了病历书写质量,33名带教教师中有29名(87.9%)教师认为培训系统提高了教学效率,所有3名教学管理人员均肯定了培训系统的质量控制功能。结论 培训系统通过智能模板、实时反馈和资源整合,有效提升了实习生病历书写质量与临床思维能力,减轻了教师负担,也提升了教学管理效率,为实习生大病历书写的数字化转型提供了一种创新方案。

关键词: 临床医学, 实习生, 病历书写, 人工智能大病历书写培训系统, 教学效果

Abstract: Objective To explore the effectiveness of an artificial intelligence (AI)-based training system for improving the quality of major medical record documentation by medical interns and enhancing teaching efficiency. Methods A total of 145 medical interns from Nanjing University Medical School Affiliated Drum Tower Hospital during the 2024-2025 academic year were selected as participants. Using a simple randomization method, they were divided into a study group (n=73) and a control group (n=72). The study group utilized the AI-based training system for medical record documentation, while the control group received traditional teaching methods. Effectiveness was evaluated through pre- and post-internship medical record assessments and satisfaction questionnaires. Data were analyzed using independent samples t-tests and descriptive statistics. Results The post-test total medical record assessment score of the study group(85.73±6.44) was higher than that of the control group (80.10±6.04), P<0.001. Questionnaire results showed that 61 (83.6%) interns in the study group believed the training system improved the quality of their medical record documentation. Among 33 teaching faculty members, 29 (87.9%) reported that the system enhanced teaching efficiency. All 3 educational administrators affirmed the system's role in quality control. Conclusions The AI-based training system, through intelligent templates, real-time feedback, and resource integration, effectively improved the quality of medical record documentation and clinical thinking skills among interns, reduced the teaching burden, and enhanced educational management efficiency. The system provides an innovative solution for the digital transformation of major medical record training for interns.

Key words: Clinical medicine, Interns, Medical record writing, AI-based medical record training system, Teaching effectiveness

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