数字医疗和数据工作:谁是数据专家?

Claus Bossen, Pernille Scholdan Bertelsen
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摘要

背景:本文报告了一项调查医疗保健领域数据专业人员的研究。这个话题既有趣又相关,因为医疗保健领域的数字化趋势和数据驱动的努力正在进行中,而这需要各种各样的数据工作:尽管人们对数据科学以及更广泛的数据工作很感兴趣,但我们对医疗保健领域数据工作者的了解却少得令人吃惊。因此,我们对丹麦一家大型国家医疗数据机构的数据工作进行了调查:方法:我们采用了一种探索性的混合方法,结合非概率技术设计了一项公开调查,目标人群为 300 多人,并进行了 11 次半结构化访谈:我们报告了与教育背景、工作身份、工作任务、员工如何获得能力和知识以及这些属性的构成有关的调查结果。我们发现了医疗保健知识、数据分析技能和信息技术等反复出现的主题,这些主题反映在教育、能力和知识方面。然而,在这些主题之内和之外存在着相当大的差异,事实上,大多数能力都是在 "工作中 "学习的,而不是作为正规教育的一部分:结论:成为一名在医疗保健领域从事数据工作的专业人员可以有不同的职业道路。最常见的工作身份是 "数据分析师";然而,各种各样的回答表明,尚未形成稳定的数据工作者身份:研究结果对教育政策制定者和医疗保健管理者具有启示意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Digital health care and data work: Who are the data professionals?

Background: This article reports on a study that investigated data professionals in health care. The topic is interesting and relevant because of the ongoing trend towards digitisation of the healthcare domain and efforts for it to become data driven, which entail a wide variety of work with data.

Objective: Despite an interest in data science and more broadly in data work, we know surprisingly little about the people who work with data in healthcare. Therefore, we investigated data work at a large national healthcare data organisation in Denmark.

Method: An explorative mixed method approach combining a non-probability technique for design of an open survey with a target population of 300+ and 11 semi-structured interviews, was applied.

Results: We report findings relevant to educational background, work identity, work tasks, and how staff acquired competences and knowledge, as well as what these attributes comprised. We found recurring themes of healthcare knowledge, data analytical skills, and information technology, reflected in education, competences and knowledge. However, there was considerable variation within and beyond those themes, and indeed most competences were learned "on the job" rather than as part of formal education.

Conclusion: Becoming a professional working with data in health care can be the result of different career paths. The most recurring work identity was that of "data analyst"; however, a wide variety of responses indicated that a stable data worker identity has not yet developed.

Implications: The findings present implications for educational policy makers and healthcare managers.

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