Educational Technologies

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
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  • Department of Education, Nanjing Drum Tower Hospital Affiliated to Nanjing University Medical School, Nanjing 210008, China

Received date: 2025-01-09

  Online published: 2025-10-30

Supported by

Special Project of Jiangsu Higher Education Society (2024JSGJ16); Higher Education Teaching Reform Research Project in Jiangsu Province for 2025 (2025JGYB335)

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.

Cite this article

Mao Kaikai , Li Xiu , Zhou Chen , Zhang Guang , Lin Yongjuan , Zhao Xiaozhi . Innovative practice of AI-empowered training for writing medical records of clinical interns[J]. Chinese Journal of Medical Education, 2025 , 45(11) : 843 -848 . DOI: 10.3760/cma.j.cn115259-20250109-00023

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