JMIR Publications

ABSTRACT

Background:

Oncology patients often face complex choices between treatment regimens with different risk benefit ratios. The 4D PICTURE 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 eight different countries.

Objective:

This paper aims to review the key ethical related to the design and development of decision-support tools in oncology.

Methods:

To explore the ethics of DSTs in cancer care, the project adopts the 'Embedded Ethics' approach: embedding ethicists into research teams to sensitize team members to ethical aspects and to assist in reflecting on those aspects throughout the project. We conducted what we call an ‘embedded review’ of the literature, as it consisted of different searches tailored to the different work packages of the 4D PICTURE project. The analysis was an iterative process involving discussions with researchers in the project.

Results:

Our review identified thirteen 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 4D PICTURE can provide insights related to 'design justice,' a novel consideration in healthcare DSTs. Ethical points of attention related to healthcare 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.

Conclusions:

This review 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 to ensure that technological innovations are designed and developed in an appropriate and patient-centred manner.