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面向临床医生的健康数据科学课程:是时候弥合技能差距了吗?

Health data science course for clinicians: Time to bridge the skills gap?

作者信息

Naderi Hafiz, Yang Yu-Hsuen, Munroe Patricia B, Petersen Steffen E, Westwood Mark, Aung Nay

机构信息

William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK.

Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, UK.

出版信息

Perfusion. 2024 Oct 11:2676591241291946. doi: 10.1177/02676591241291946.

Abstract

BACKGROUND

Data science skills are highly relevant for clinicians working in an era of big data in healthcare. However, these skills are not routinely taught, representing a growing unmet educational need. This education report presents a structured short course that was run to teach clinicians data science and the lessons learnt.

METHODS

A 1-day introductory course was conducted within a tertiary hospital in London. It consisted of lectures followed by facilitated pair programming exercises in R, an object-oriented programming language. Feedback was collated and participant responses were graded using a Likert scale.

RESULTS

The course was attended by 20 participants. The majority of participants (69%) were in higher speciality cardiology training. While more than half of the participants (56%) received prior training in statistics either through formal taught programmes (e.g., a Master's degree) or online courses, the participants reported several barriers to expanding their skills in data science due to limited programming skills, lack of dedicated time, training opportunities and awareness. After the short course, there was a significant increase in participants' self-rated confidence in using R for data analysis (mean response; before the course: 1.69 ± 1.0, after the course: 3.2 ± 0.9, = .0005) and awareness of the capabilities of R (mean response; before the course: 2.1 ± 0.9, after the course: 3.6 ± 0.7, = .0001, on a 5-point Likert scale).

CONCLUSION

This proof-of-concept study demonstrates that a structured short course can effectively introduce data science skills to clinicians and supports future educational initiatives to integrate data science teaching into medical education.

摘要

背景

在医疗保健大数据时代,数据科学技能与临床医生密切相关。然而,这些技能并非常规教学内容,这一教育需求日益凸显且未得到满足。本教育报告介绍了一门为教授临床医生数据科学而开设的结构化短期课程以及所吸取的经验教训。

方法

在伦敦的一家三级医院举办了为期一天的入门课程。课程包括讲座,随后是在R(一种面向对象编程语言)中进行的结对编程练习,并提供指导。收集了反馈意见,并使用李克特量表对参与者的回答进行评分。

结果

20名参与者参加了该课程。大多数参与者(69%)正在接受高级心脏病专科培训。虽然超过一半的参与者(56%)通过正规教学课程(如硕士学位)或在线课程接受过统计学方面的前期培训,但由于编程技能有限、缺乏专门时间、培训机会和相关意识,参与者报告在提升数据科学技能方面存在诸多障碍。短期课程结束后,参与者在使用R进行数据分析方面的自我评估信心显著提高(平均得分;课程前:1.69±1.0,课程后:3.2±0.9,P =.0005),对R功能的认识也有所提高(平均得分;课程前:2.1±0.9,课程后:3.6±0.7,P =.0001,采用5分李克特量表)。

结论

这项概念验证研究表明,结构化短期课程能够有效地向临床医生介绍数据科学技能,并为未来将数据科学教学纳入医学教育的教育举措提供支持。

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