Teaching practice and exploration of the optional course of medical informatics for non-informatics students in medical colleges and universities

Zhao Xiangkun; Jing Bin; Liu Dongdong; Chen Hui; Liu Honglei

doi:10.3760/cma.j.cn116021-20220411-01536

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Teaching practice and exploration of the optional course of medical informatics for non-informatics students in medical colleges and universities

Teaching Reform | 更新时间：2023-12-26

- Teaching practice and exploration of the optional course of medical informatics for non-informatics students in medical colleges and universities
- Chinese Journal of Medical Education Research Vol. 22, Issue 12, Pages: 1851-1854(2023)
- 作者机构：
  
  首都医科大学生物医学信息学系计算机教研室，北京　100069
- 作者简介：
  
  Liu Dongdong, Email: pqu2@163.com
- 基金信息：
  
  Science and Technology Plan of Beijing Municipal Education Commission(KM202010025025)
- DOI：10.3760/cma.j.cn116021-20220411-01536
  CLC： R-05
- Published：20 December 2023，
  
  Received：11 April 2022，
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赵相坤, 景斌, 刘冬冬, 等. 医学院校非信息类专业医学信息学选修课的教学实践研究[J]. 中华医学教育探索杂志, 2023, 22(12): 1851-1854.

Zhao Xiangkun, Jing Bin, Liu Dongdong, et al. Teaching practice and exploration of the optional course of medical informatics for non-informatics students in medical colleges and universities. [J]. Chinese Journal of Medical Education Research 22(12):1851-1854(2023)
赵相坤, 景斌, 刘冬冬, 等. 医学院校非信息类专业医学信息学选修课的教学实践研究[J]. 中华医学教育探索杂志, 2023, 22(12): 1851-1854. DOI： 10.3760/cma.j.cn116021-20220411-01536.

Zhao Xiangkun, Jing Bin, Liu Dongdong, et al. Teaching practice and exploration of the optional course of medical informatics for non-informatics students in medical colleges and universities. [J]. Chinese Journal of Medical Education Research 22(12):1851-1854(2023) DOI： 10.3760/cma.j.cn116021-20220411-01536.

摘要

以移动互联网、物联网、云计算、大数据等为代表的新一代信息技术与健康医疗行业紧密融合，对医学院校面向非信息类专业的医学信息学选修课提出了更高的教学目标和内容要求。本文结合实际教学需求和临床医学生培养目标，对医学信息学选修课的教学内容进行了科学地优化和配置。选择医学信息学教育中的“小数据集，电子病历/电子健康档案的基本应用”为主要内容，模块化医学信息处理中的数值型数据、文本型数据和图像数据，以案例驱动和翻转课堂变革教学方式，将机器学习中常见的方法（如回归、分类和聚类方法）根植于案例的解决方案中，以综合的算法实例报告作为课程考核评价方式。实践表明，以上探索既激发了学生对医学信息学选修课的兴趣，又有效贯彻了医学生培养早预测、早调整、早发现、早诊断和早治疗的“五早”模式。

Abstract

Nowadays

the new healthcare industry is closely integrated with the new-generation information techniques such as mobile Internet

Internet of things

cloud computing

and big data

which proposes higher requirements for the teaching objectives and contents of the optional course of medical informatics for non-informatics students in medical colleges and universities. Based on the actual teaching demands and the training objectives of clinical medical students

the teaching contents of the optional course of medical informatics were scientifically optimized and allocated. With "small datasets and basic application of electronic medical records/electronic health records" in medical informatics education as the main contents

numeric data

text data

and image data were modularized in medical information processing

and the methods of flipped classroom and case-driven teaching were adopted. The commonly used methods in machine learning (such as regression

classification

and clustering methods) were introduced and applied in task-based case studies

and the comprehensive algorithm case report was used for course assessment and evaluation. The teaching practice has shown that the above exploration not only stimulated the interest in the optional course of medical informatics among students

but also effectively implemented the "five early" mode of early prediction

early adjustment

early identification

early diagnosis

and early treatment among medical students.

关键词

医学信息学实践和探究模块化预测

Keywords

Medical InformaticsPractice and explorationModularizationPrediction

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