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肿瘤学学习型医疗保健系统治理:患者建议。

Governance of a Learning Health Care System for Oncology: Patient Recommendations.

机构信息

University of Michigan, Ann Arbor, MI.

American Society of Clinical Oncology, Alexandria, VA.

出版信息

JCO Oncol Pract. 2021 Apr;17(4):e479-e489. doi: 10.1200/OP.20.00454. Epub 2020 Oct 23.

Abstract

PURPOSE

The learning health care system (LHS) was designed to enable real-time learning and research by harnessing data generated during patients' clinical encounters. This novel approach begets ethical questions regarding the oversight of users and uses of patient data. Understanding patients' perspectives is vitally important.

MATERIALS AND METHODS

We conducted democratic deliberation sessions focused on CancerLinQ, a real-world LHS. Experts presented educational content, and then small group discussions were held to elicit viewpoints. The deliberations centered around whether policies should permit or deny certain users and uses of secondary data. De-identified transcripts of the discussions were examined by using thematic analysis.

RESULTS

Analysis identified two thematic clusters: expectations and concerns, which seemed to inform LHS governance recommendations. Participants expected to benefit from the LHS through the advancement of medical knowledge, which they hoped would improve treatments and the quality of their care. They were concerned that profit-driven users might manipulate the data in ways that could burden or exploit patients, hinder medical decisions, or compromise patient-provider communication. It was recommended that restricted access, user fees, and penalties should be imposed to prevent users, especially for-profit entities, from misusing data. Another suggestion was that patients should be notified of potential ethical issues and included on diverse, unbiased governing boards.

CONCLUSION

If patients are to trust and support LHS endeavors, their concerns about for-profit users must be addressed. The ethical implementation of such systems should consist of patient representation on governing boards, transparency, and strict oversight of for-profit users.

摘要

目的

学习型医疗保健系统(LHS)旨在通过利用患者临床就诊时生成的数据,实现实时学习和研究。这种新方法引发了关于用户监督和患者数据使用的伦理问题。了解患者的观点至关重要。

材料与方法

我们进行了以 CancerLinQ 为重点的民主审议会议,CancerLinQ 是一个真实世界的 LHS。专家们介绍了教育内容,然后进行小组讨论以引出观点。审议集中在政策是否应该允许或拒绝某些用户对二次数据的使用。对讨论的匿名记录进行了主题分析。

结果

分析确定了两个主题集群:期望和关注点,这似乎为 LHS 治理建议提供了信息。参与者期望通过医学知识的进步从 LHS 中受益,他们希望这将改善治疗方法和他们的护理质量。他们担心以利润为导向的用户可能会以可能给患者带来负担或剥削、阻碍医疗决策或损害患者与提供者沟通的方式操纵数据。有人建议应限制访问、收取用户费用和实施处罚,以防止用户(特别是营利实体)滥用数据。另一个建议是应通知患者潜在的道德问题,并让他们加入多元化、公正的管理委员会。

结论

如果患者要信任和支持 LHS 的努力,就必须解决他们对营利性用户的担忧。此类系统的道德实施应包括患者在管理委员会中的代表、透明度和对营利性用户的严格监督。

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