改善癌症治疗的数据驱动决策支持工具的伦理设计:4D PICTURE项目的嵌入式伦理审查。

IF 2.7 Q2 ONCOLOGY
JMIR Cancer Pub Date : 2025-04-10 DOI:10.2196/65566
Marieke Bak, Laura Hartman, Charlotte Graafland, Ida J Korfage, Alena Buyx, Maartje Schermer
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引用次数: 0

摘要

肿瘤患者经常面临不同风险-收益比的治疗方案之间的复杂选择。4D PICTURE(通过以用户为中心的研究产生改善的癌症结果)项目旨在通过为乳腺癌、前列腺癌和黑色素瘤患者开发数据驱动的决策支持工具(DSTs)来支持患者、他们的家人和临床医生做出这些复杂的决策,作为使用称为MetroMapping的方法重新设计护理路径的一部分。由于该项目将创建数据驱动的预后模型,并使用人工智能开发对话工具,同时通过在8个不同国家建立经验丰富的专家委员会,包括患者的观点,因此需要考虑无数的伦理问题。本文旨在回顾与肿瘤学中DSTs的设计和开发相关的关键伦理挑战。为了探索DSTs在癌症治疗中的伦理问题,该项目采用了嵌入伦理方法——将伦理学家嵌入研究团队,使团队成员对伦理问题敏感,并在整个项目中帮助他们反思这些问题。我们从与4D PICTURE项目的不同工作包相关的主题的关键文献中对项目进行了我们所谓的嵌入式审查,而分析是一个涉及与项目研究人员讨论的迭代过程。我们的综述确定了13个关键的伦理挑战,这些挑战与发展DSTs和重新设计治疗路径以实现更个性化的癌症治疗有关。几个伦理方面与数据偏差和隐私的一般潜在问题有关,但引发了具体的研究问题,例如,关于在模型中包含某些人口变量的问题。4D PICTURE项目中的设计方法可以提供与设计公正相关的见解,这是医疗保健DSTs的一种新考虑。与卫生保健政策相关的伦理关注点,如成本效益、财务可持续性和环境影响,以及研究过程本身的挑战,也被确定,强调了认识正义的重要性、嵌入伦理学家的作用和心理安全。这一观点强调了以前在数字健康伦理文献中被忽视的伦理方面,并在一个正在进行的项目中放大了现实世界的挑战。它强调了数据驱动型医学研究项目的研究人员和领导者需要解决项目科学核心之外的伦理挑战。更一般地说,我们量身定制的审查方法为从一开始就将伦理嵌入到大型数据驱动的肿瘤学研究项目中提供了一种模式,这有助于确保以适当和以患者为中心的方式设计和开发技术创新。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Ethical Design of Data-Driven Decision Support Tools for Improving Cancer Care: Embedded Ethics Review of the 4D PICTURE Project.

Ethical Design of Data-Driven Decision Support Tools for Improving Cancer Care: Embedded Ethics Review of the 4D PICTURE Project.

Ethical Design of Data-Driven Decision Support Tools for Improving Cancer Care: Embedded Ethics Review of the 4D PICTURE Project.

Ethical Design of Data-Driven Decision Support Tools for Improving Cancer Care: Embedded Ethics Review of the 4D PICTURE Project.

Oncology patients often face complex choices between treatment regimens with different risk-benefit ratios. The 4D PICTURE (Producing Improved Cancer Outcomes Through User-Centered Research) project aims to support patients, their families, and clinicians with these complex decisions by developing data-driven decision support tools (DSTs) for patients with breast cancer, prostate cancer, and melanoma as part of care path redesign using a methodology called MetroMapping. There are myriad ethical issues to consider as the project will create data-driven prognostic models and develop conversation tools using artificial intelligence while including patient perspectives by setting up boards of experiential experts in 8 different countries. This paper aims to review the key ethical challenges related to the design and development of DSTs in oncology. To explore the ethics of DSTs in cancer care, the project adopted the Embedded Ethics approach-embedding ethicists into research teams to sensitize team members to ethical aspects and assist in reflecting on those aspects throughout the project. We conducted what we call an embedded review of the project drawing from key literature on topics related to the different work packages of the 4D PICTURE project, whereas the analysis was an iterative process involving discussions with researchers in the project. Our review identified 13 key ethical challenges related to the development of DSTs and the redesigning of care paths for more personalized cancer care. Several ethical aspects were related to general potential issues of data bias and privacy but prompted specific research questions, for instance, about the inclusion of certain demographic variables in models. Design methodology in the 4D PICTURE project can provide insights related to design justice, a novel consideration in health care DSTs. Ethical points of attention related to health care policy, such as cost-effectiveness, financial sustainability, and environmental impact, were also identified, along with challenges in the research process itself, emphasizing the importance of epistemic justice, the role of embedded ethicists, and psychological safety. This viewpoint highlights ethical aspects previously neglected in the digital health ethics literature and zooms in on real-world challenges in an ongoing project. It underscores the need for researchers and leaders in data-driven medical research projects to address ethical challenges beyond the scientific core of the project. More generally, our tailored review approach provides a model for embedding ethics into large data-driven oncology research projects from the start, which helps ensure that technological innovations are designed and developed in an appropriate and patient-centered manner.

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来源期刊
JMIR Cancer
JMIR Cancer ONCOLOGY-
CiteScore
4.10
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0.00%
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64
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12 weeks
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