Foreign and Comparative Medical Education

Comparison of medical data science courses in comprehensive universities at home and abroad

  • Fang Linhan ,
  • Cheng Qi ,
  • Ning Peishan ,
  • Hu Guoqing
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  • Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410013, China

Received date: 2025-10-18

  Online published: 2026-05-28

Supported by

2025 Medical Education Research Projects Approved by the Medical Education Branch of the Chinese Medical Association and the National Centre for Medical Education Development(2025A09)

Abstract

Objective To compare medical data science courses offered in comprehensive universities at home and abroad, and to provide references for optimizing the relevant curricula in Chinese universities. Methods A text analysis method was adopted. Curricula of medical-related programs from 25 comprehensive universities domestic and international were included. Programs containing medical data science courses were screened, and relevant information was extracted. Descriptive statistics were used to compare differences between China and other countries. Results A total of 225 medical data science courses were identified across the 25 comprehensive universities, including 112 in China and 113 abroad. Regarding target students, undergraduate courses accounted for 48.2% (54/112) in China, which was higher than 17.7% (20/113) abroad. In terms of course setting, compulsory courses represented 45.5% (51/112) in China, lower than 69.9% (79/113) abroad. Regarding credits, most courses in China were within the [2,4) credit range, very few courses worth 4 credits or more, whereas the vast majority of courses abroad were worth 4 credits or more. For course category, courses on data governance, ethics, and security accounted for only 1.8% (2/112) in China, significantly lower than 9.7% (11/113) abroad. Conclusions Although the number of medical data science courses is similar between China and other countries, notable differences exist. Chinese universities offer broader undergraduate access and a higher proportion of elective courses with a flexible credit configuration, which have the advantages of exposing students to data science at an early stage and providing curricular flexibility. However, they are insufficient in courses on data governance, ethics, and security.

Cite this article

Fang Linhan , Cheng Qi , Ning Peishan , Hu Guoqing . Comparison of medical data science courses in comprehensive universities at home and abroad[J]. Chinese Journal of Medical Education, 2026 , 46(6) : 476 -480 . DOI: 10.3760/cma.j.cn115259-20251018-01313

References

[1] Seth P, Hueppchen N, Miller SD, et al. Data science as a core competency in undergraduate medical education in the age of artificial intelligence in health care[J]. JMIR Med Educ, 2023,9:e46344. DOI: 10.2196/46344.
[2] 余灿清, 李立明. 大型队列研究中的数据科学[J].中华流行病学杂志,2019,40(1):1-4. DOI: 10.3760/cma.j.issn.0254-6450.2019.01.001.
[3] 朝乐门. 数据科学[M]. 2版 .北京:清华大学出版社,2024:7-23.
[4] Goldsmith J, Sun Y, Fried LP, et al. The emergence and future of public health data science[J]. Public Health Rev, 2021,42:1604023. DOI: 10.3389/phrs.2021.1604023.
[5] Yeh CY, Wall DP, Matthys K, et al. Curriculum design in an evolving field: perspectives on biomedical data science from Stanford[J]. Annu Rev Biomed Data Sci, 2025,8(1):341-354. DOI: 10.1146/annurev-biodatasci-090624-022951.
[6] 范美玉. 健康数据科学学科建设现状及在健康医疗领域的应用[J].中国社会医学杂志,2023,40(5):519-521. DOI: 10.3969/j.issn.1673-5625.2023.05.004.
[7] 关庆娟, 王磊. 数智时代“医学+数据科学”复合型创新人才培养路径探索[J].科技风,2025(8):71-74. DOI: 10.19392/j.cnki.1671-7341.202508024.
[8] 欧阳东, 陈玉云, 赵云, 等. 医学院校中“数据科学导论”课程建设的研究[J].科技资讯,2024,22(20):224-227,242. DOI: 10.16661/j.cnki.1672-3791.2405-5042-2179.
[9] 软科. 2025中国大学排名[EB/OL].(2025-09-25)[2025-09-29].https://www.shanghairanking.cn/rankings/bcur/2025.
[10] QS TOP UNIVERSITIES. QS world university rankings 2025[EB/OL].(2024-06-05)[2025-09-29]. https://www.topuniversities.com/world-university-rankings/2025.
[11] 朝乐门, 杨灿军, 王盛杰, 等. 全球数据科学课程建设现状的实证分析[J].数据分析与知识发现,2017,1(6):12-21.
[12] 覃雄派.数据科学概论[M]. 2版.北京:中国人民大学出版社,2022:1-7.
[13] Shockang.数据计算、数据分析和数据挖掘有什么区别?[EB/OL].(2023-05-21)[2025-09-29]. https://blog.csdn.net/Shockang/article/details/130797745.
[14] 梁彦. 中欧学分测算方法的比较分析[J].世界教育信息,2023,36(7):12-21. DOI: 10.3969/j.issn.1672-3937.2023.07.02.
[15] Yang C, Chen Y, Qian C, et al. The data-intensive research paradigm: challenges and responses in clinical professional graduate education[J]. Front Med (Lausanne), 2025,12:1461863. DOI: 10.3389/fmed.2025.1461863.
[16] 张雪, 张志强, 陈秀娟. 中美医学信息学本硕教育现状对比分析与启示[J].图书情报工作,2019,63(12):12-21. DOI: 10.13266/j.issn.0252-3116.2019.12.002.
[17] 窦现金. 欧盟学分认定、累计与转换体系的发展[J].世界教育信息,2018,31(7):50-54.
[18] Ma M, Li Y, Gao L, et al. The need for digital health education among next-generation health workers in China: a cross-sectional survey on digital health education[J]. BMC Med Educ, 2023,23(1):541. DOI: 10.1186/s12909-023-04407-w.
[19] Ahmed MM, Okesanya OJ, Oweidat M, et al. The ethics of data mining in healthcare: challenges, frameworks, and future directions[J]. BioData Min, 2025,18(1):47. DOI: 10.1186/s13040-025-00461-w.
[20] Hasan HE, Alzoubi KH, Khabour OF, et al. Perceived clinical and ethical impact of digital transformation in healthcare and research: a survey in the MENA region[J]. PLoS One, 2025,20(12):e0336618. DOI: 10.1371/journal.pone.0336618.
[21] Baumer BS, Garcia RL, Kim AY, et al. Integrating data science ethics into an undergraduate major: a case study[J]. Journal of Statistics and Data Science Education, 2022,30(1):15-28. DOI: 10.1080/26939169.2022.2038041.
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