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设定风险限制,确保学习型医疗保健的公平性。

Setting Risk Limits and Ensuring Fairness in Learning Health Care.

出版信息

Hastings Cent Rep. 2022 May;52(3):34-36. doi: 10.1002/hast.1395.

DOI:10.1002/hast.1395
PMID:35763205
Abstract

Historical abuses resulted in the segregation of clinical research and clinical care. While this approach has protected participants, it is extremely inefficient, leading commentators to propose (re)integrating research and care into learning health care systems. Previous commentators have argued that, in these systems, it could be appropriate to condition care on patients' consent to participation in research, but only when the added research risks are minimal. In the article "Compulsory Research in Learning Health Care: Against a Minimal Risk Limit," Robert Steel agrees about making research participation a condition for receiving care in these systems, but he argues that the limit to minimal risks is unfounded, and he offers compelling reasons to think that, in principle, permitting greater research risks could be fair and consistent with individual rights. Unfortunately, the nature of current institutions suggests that this approach is unlikely to be implemented fairly. We conclude that, to ensure fair learning health care systems, research and care may need to be reformed in more fundamental ways.

摘要

历史上的虐待导致临床研究和临床护理的隔离。虽然这种方法保护了参与者,但它极其低效,导致评论员提议(重新)将研究和护理整合到学习型医疗保健系统中。以前的评论员认为,在这些系统中,在患者同意参与研究的情况下,可以将护理作为条件,但前提是增加的研究风险最小。在文章“学习型医疗保健中的强制性研究:反对最小风险限制”中,Robert Steel 同意在这些系统中使研究参与成为获得护理的条件,但他认为最小风险限制是没有根据的,他提出了令人信服的理由认为,原则上,允许更大的研究风险可能是公平的,并符合个人权利。不幸的是,当前机构的性质表明,这种方法不太可能得到公平实施。我们的结论是,为了确保公平的学习型医疗保健系统,研究和护理可能需要以更根本的方式进行改革。

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