Objective Identifying ethical concerns with ML applications to healthcare (ML-HCA) before problems arise is now a stated goal of ML design oversight groups and regulatory agencies. Lack of accepted standard methodology for ethical analysis, however, presents challenges. In this case study, we evaluate use of a stakeholder “values-collision” approach to identify consequential ethical challenges associated with an ML-HCA for advanced care planning (ACP). Identification of ethical challenges could guide revision and improvement of the ML-HCA. Materials and Methods We conducted semistructured interviews of the designers, clinician-users, affiliated administrators, and patients, and inductive qualitative analysis of transcribed interviews using modified grounded theory. Results Seventeen stakeholders were interviewed. Five “values-collisions”—where stakeholders disagreed about decisions with ethical implications—were identified: (1) end-of-life workflow and how model output is introduced; (2) which stakeholders receive predictions; (3) benefit-harm trade-offs; (4) whether the ML design team has a fiduciary relationship to patients and clinicians; and, (5) how and if to protect early deployment research from external pressures, like news scrutiny, before research is completed. Discussion From these findings, the ML design team prioritized: (1) alternative workflow implementation strategies; (2) clarification that prediction was only evaluated for ACP need, not other mortality-related ends; and (3) shielding research from scrutiny until endpoint driven studies were completed. Conclusion In this case study, our ethical analysis of this ML-HCA for ACP was able to identify multiple sites of intrastakeholder disagreement that mark areas of ethical and value tension. These findings provided a useful initial ethical screening.

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This article explores ethical issues raised by Primary Care Physicians (PCPs) when diagnosing depression and caring for cross-cultural patients. This study was conducted in three primary care clinics within a major metropolitan area in the Southeastern United States. The PCPs were from a variety of ethnocultural backgrounds including South Asian, Hispanic, East Asian and Caucasian. While medical education training and guidelines aim to teach physicians about the nuances of cross-cultural patient interaction, PCPs report that past experiences guide them in navigating cross-cultural conversations and patient care. In this study, semi-structured interviews were conducted with seven PCPs which were transcribed and underwent thematic analysis to explore how patients’ cultural backgrounds and understanding of depression affected PCPs’ reasoning and diagnosing of depression in patients from different cultural backgrounds. Ethical issues that arose included: limiting treatment options, expressing a patient’s mental health diagnosis in a biomedical sense to reduce stigma, and somatization of mental health symptoms. Ethical implications, such as lack of autonomy, unnecessary testing, and the possible misuse of healthcare resources are discussed.