医学教育管理 ›› 2020, Vol. 6 ›› Issue (6): 591-594.doi: 10.3969/j.issn.2096-045X.2020.06.016

• 毕业后教育 • 上一篇    下一篇

利用基于人工智能的临床决策支持系统提升住院医师规范化培训质量

贾  茜,  李小莹   

  1. 首都医科大学宣武医院医务处,北京 100053
  • 收稿日期:2020-10-26 出版日期:2020-12-20 发布日期:2021-01-05

Using clinical decision support system based on artificial intelligence to improve standardized training of residents

Jia Qian, Li Xiaoying   

  1. Medical Affairs Office, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
  • Received:2020-10-26 Online:2020-12-20 Published:2021-01-05

摘要: 某医院依据国家卫生健康委发布的疾病病种管理质控指标、病历书写基本规范、住院病案首页数据填写质量规范制定质控规则。采用自然语言处理技术建立基于人工智能的临床决策支持系统(clinical decision support system,CDSS)系统,无缝衔接于电子病历系统中。住院医师在书写电子病历时,系统依据书写内容实时进行判断,及时发现诊治缺陷并将建议形成消息弹窗提醒,纠正病历记录中的错误,完善病历书写,保证病案首页填写质量。系统使用后,质控指标达成率较前明显提升,病历缺陷率明显下降,有效提升住院医师疾病诊治及病历书写规范性。

关键词: 住院医师培训,  人工智能,  临床决策支持系统,  电子病历

Abstract: According to the quality control index of disease and disease management issued by the National Health Commission, the basic standard of medical record writing, and the quality specification of data filling in the front page of inpatient medical record, a hospital formulates quality control rules. The  clinical decision support system (CDSS) system based on artificial intelligence was established by natural language processing technology, and was seamlessly connected to the electronic medical record system. When residents write electronic medical records, the system makes real-time judgment of writing content, finds out the diagnosis and treatment defects in time, and forms a message pop-up reminder to correct the errors in the medical records, improves the medical record writing, and ensures the quality of filling in the front page of medical records. After using the system, the achievement rate of quality control indicators was significantly improved, and the defect rate of medical records was significantly decreased, which effectively improved the standardization of disease diagnosis and treatment and medical record writing of residents.

Key words: resident training,  artificial intelligence, clinical decision support system, electronic medical records

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