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

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.