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本文引用的文献

1
Patient Preferences Regarding Informed Consent Models for Participation in a Learning Health Care System for Oncology.患者对参与肿瘤学学习型医疗保健系统的知情同意模式的偏好。
JCO Oncol Pract. 2020 Sep;16(9):e977-e990. doi: 10.1200/JOP.19.00300. Epub 2020 Apr 30.
2
Sharing Health Care Data With Digital Giants: Overcoming Obstacles and Reaping Benefits While Protecting Patients.与数字巨头共享医疗保健数据:在保护患者的同时克服障碍并收获益处。
JAMA. 2020 Feb 11;323(6):507-508. doi: 10.1001/jama.2019.21215.
3
Sharing Patient Data Without Exploiting Patients.共享患者数据而不剥削患者。
JAMA. 2020 Feb 11;323(6):505-506. doi: 10.1001/jama.2019.22354.
4
Patients' and public views and attitudes towards the sharing of health data for research: a narrative review of the empirical evidence.患者和公众对健康数据用于研究的看法和态度:实证证据的叙述性综述。
J Med Ethics. 2022 Jan;48(1):3-13. doi: 10.1136/medethics-2019-105651. Epub 2019 Nov 12.
5
Effect of Public Deliberation on Patient Attitudes Regarding Consent and Data Use in a Learning Health Care System for Oncology.公众讨论对肿瘤学学习型医疗保健系统中患者对同意和数据使用的态度的影响。
J Clin Oncol. 2019 Dec 1;37(34):3203-3211. doi: 10.1200/JCO.19.01693. Epub 2019 Oct 2.
6
Big Data, Big Tech, and Protecting Patient Privacy.大数据、大型科技公司与保护患者隐私
JAMA. 2019 Sep 24;322(12):1141-1142. doi: 10.1001/jama.2019.11365.
7
CancerLinQ: Origins, Implementation, and Future Directions.癌症LinQ:起源、实施及未来方向。
JCO Clin Cancer Inform. 2018 Dec;2:1-7. doi: 10.1200/CCI.17.00060.
8
Health Research with Big Data: Time for Systemic Oversight.大数据健康研究:进行系统性监督的时候了。
J Law Med Ethics. 2018 Mar;46(1):119-129. doi: 10.1177/1073110518766026. Epub 2018 Mar 27.
9
Perspectives of Patients With Cancer on the Ethics of Rapid-Learning Health Systems.癌症患者对快速学习型卫生系统伦理的看法。
J Clin Oncol. 2017 Jul 10;35(20):2315-2323. doi: 10.1200/JCO.2016.72.0284. Epub 2017 May 24.
10
Patient Perspectives on the Ethical Implementation of a Rapid Learning System for Oncology Care.患者对肿瘤护理快速学习系统伦理实施的看法。
J Oncol Pract. 2017 Mar;13(3):e163-e175. doi: 10.1200/JOP.2016.016782. Epub 2017 Jan 24.

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.

DOI:10.1200/OP.20.00454
PMID:33095694
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8257992/
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。