"Data makes the story come to life:" understanding the ethical and legal implications of Big Data research involving ethnic minority healthcare workers in the United Kingdom-a qualitative study.
"Data makes the story come to life:" understanding the ethical and legal implications of Big Data research involving ethnic minority healthcare workers in the United Kingdom-a qualitative study.
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DOI：
10.1186/s12910-022-00875-9
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发表时间：
2022-12-16
影响因子：
2.7
通讯作者：
Pareek, Manish
中科院分区：
文献类型：
--
作者：
Dove, Edward;Reed-Berendt, Ruby;Pareek, Manish
UK-REACH（“英国对医护人员的种族和 COVID-19 结果的研究”）的目的是了解英国 (UK) 来自少数族裔群体的医护人员 (HCW) 是否、如何以及为何面临更高的 COVID-19 不良结果风险。在本文中，我们介绍了该研究的伦理和法律流的结果，该研究进行了定性研究，旨在理解和解决与医护人员注册数据和医疗数据链接相关的数据保护、隐私和信息治理的法律、伦理和社会可接受性问题。我们通过二对一的半结构化访谈采访了来自英国各地的 22 位医疗保健和健康研究领域的关键意见领袖。使用定性主题分析对成绩单进行编码。参与者告诉我们，公共卫生大数据研究的一个重要方面是不同的不信任驱动因素——对研究本身、研究人员和资助者的不信任，以及参与者社区内更广泛的不信任担忧，特别是在 COVID-19 的背景下和那些处于更边缘化社区环境中的人们。然而，尽管面临挑战，参与者还确定了可以制定合法且符合道德的研究方法的方法，以减轻或克服不信任并建立对大数据公共卫生研究的更大信心。总体而言，我们的研究表明，该领域的“大数据伦理设计”研究方法有助于确保（1）有意义的社区和参与者参与正在发生，现有的挑战得到解决，（2）任何新的挑战或迄今为止未知的未知因素都可以得到快速、适当的考虑，以确保潜在（但实质性）的危害被识别并在必要时最小化。我们的研究结果表明，这种方法反过来将有助于推动更好的科学突破，转化为医学创新和有效的公共卫生干预措施，从而使所研究的公众受益，包括那些经常在研究中被边缘化的公众。在线版本包含可在 10.1186/s12910-022-00875-9 获取的补充材料。
The aim of UK-REACH (“The United Kingdom Research study into Ethnicity And COVID-19 outcomes in Healthcare workers”) is to understand if, how, and why healthcare workers (HCWs) in the United Kingdom (UK) from ethnic minority groups are at increased risk of poor outcomes from COVID-19. In this article, we present findings from the ethical and legal stream of the study, which undertook qualitative research seeking to understand and address legal, ethical, and social acceptability issues around data protection, privacy, and information governance associated with the linkage of HCWs’ registration data and healthcare data. We interviewed 22 key opinion leaders in healthcare and health research from across the UK in two-to-one semi-structured interviews. Transcripts were coded using qualitative thematic analysis. Participants told us that a significant aspect of Big Data research in public health is varying drivers of mistrust—of the research itself, research staff and funders, and broader concerns of mistrust within participant communities, particularly in the context of COVID-19 and those situated in more marginalised community settings. However, despite the challenges, participants also identified ways in which legally compliant and ethically informed approaches to research can be crafted to mitigate or overcome mistrust and establish greater confidence in Big Data public health research. Overall, our research indicates that a “Big Data Ethics by Design” approach to research in this area can help assure (1) that meaningful community and participant engagement is taking place and that extant challenges are addressed, and (2) that any new challenges or hitherto unknown unknowns can be rapidly and properly considered to ensure potential (but material) harms are identified and minimised where necessary. Our findings indicate such an approach, in turn, will help drive better scientific breakthroughs that translate into medical innovations and effective public health interventions, which benefit the publics studied, including those who are often marginalised in research. The online version contains supplementary material available at 10.1186/s12910-022-00875-9.
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