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健康研究的数据信托可以从生物库的参与式治理中学到什么?

What can data trusts for health research learn from participatory governance in biobanks?

机构信息

Society and Ethics Research, Wellcome Genome Campus, Cambridge, UK

Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.

出版信息

J Med Ethics. 2022 May;48(5):323-328. doi: 10.1136/medethics-2020-107020. Epub 2021 Mar 19.

Abstract

New models of data governance for health data are a focus of growing interest in an era of challenge to the social licence. In this article, we reflect on what the data trust model, which is founded on principles of participatory governance, can learn from experiences of involving and engagement of members of the public and participants in the governance of large-scale biobanks. We distinguish between upstream and ongoing governance models, showing how they require careful design and operation if they are to deliver on aspirations for deliberation and participation. Drawing on this learning, we identify a set of considerations important to future design for data trusts as they seek to ensure just, proportionate and fair governance. These considerations relate to the timing of involvement of participants, patterns of inclusion and exclusion, and responsiveness to stakeholder involvement and engagement. We emphasise that the evolution of governance models for data should be matched by a commitment to evaluation.

摘要

在社会许可受到挑战的时代,健康数据的数据治理新模式受到越来越多的关注。在本文中,我们反思了基于参与式治理原则的数据信托模式可以从公众成员和大型生物库治理参与者的参与和参与经验中学到什么。我们区分了上游和持续的治理模式,展示了如果要实现审议和参与的愿望,它们需要精心设计和运作。借鉴这一学习成果,我们确定了一套对于数据信托未来设计很重要的考虑因素,因为它们试图确保公正、相称和公平的治理。这些考虑因素涉及参与者参与的时间安排、包容和排斥的模式,以及对利益相关者参与和参与的响应。我们强调,数据治理模式的演变应配以对评估的承诺。

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