Oncological big data platforms for promoting digital competencies and professionalism in Chinese medical students: a cross-sectional study. Issue 9 (15th September 2022)

• Record Type: Journal Article
• Authors: Liu, Jiahao; Jiao, Xiaofei; Zeng, Shaoqing; Li, Huayi; Jin, Ping; Chi, Jianhua; Liu, Xingyu; Yu, Yang; Ma, Guanchen; Zhao, Yingjun; Li, Ming; Peng, Zikun; Huo, Yabing; Gao, Qing-Lei
• Is Part Of: BMJ open. Volume 12:Issue 9(2022)
• Publication Date: 2022-09-15
• Subjects: MEDICAL EDUCATION & TRAINING -- Gynaecological oncology -- Gynaecological oncology -- Health informatics; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2022-061015
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Objectives: Advancements in big data technology are reshaping the healthcare system in China. This study aims to explore the role of medical big data in promoting digital competencies and professionalism among Chinese medical students. Design, setting and participants: This study was conducted among 274 medical students who attended a workshop on medical big data conducted on 8 July 2021 in Tongji Hospital. The workshop was based on the first nationwide multifunction gynecologic oncology medical big data platform in China, at the National Union of Real-World Gynecologic Oncology Research & Patient Management Platform (NUWA platform). Outcome measures: Data on knowledge, attitudes towards big data technology and professionalism were collected before and after the workshop. We have measured the four skill categories: doctor‒patient relationship skills, reflective skills, time management and interprofessional relationship skills using the Professionalism Mini-Evaluation Exercise (P-MEX) as a reflection for professionalism. Results: A total of 274 students participated in this workshop and completed all the surveys. Before the workshop, only 27% of them knew the detailed content of medical big data platforms, and 64% knew the potential application of medical big data. The majority of the students believed that big data technology is practical in their clinical practice (77%), medical education (85%) and scientific research (82%). Over 80% of the participants showed positive attitudes toward big data platforms. They also exhibited sufficient professionalism before the workshop. Meanwhile, the workshop significantly promoted students' knowledge of medical big data (p< 0.05 ), and led to more positive attitudes towards big data platforms and higher levels of professionalism. Conclusions: Chinese medical students have primitive acquaintance and positive attitudes toward big data technology. The NUWA platform-based workshop may potentially promote their understanding of big data and enhance professionalism, according to the self-measured P-MEX scale.