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Competing Interests: Intérêts concurrents :: Aucun déclaré.

Competing Interests: Competing interests:: None declared.

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., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Rapid genome-wide sequencing (rGWS) is being increasingly used to aid in prognostication and decision-making for critically ill newborns and children. Although its feasibility in this fast-paced setting has been described, this new paradigm of inpatient genetic care raises new ethical challenges., Objective: A scoping review was performed to (1) identify salient ethical issues in this area of practice; and (2) bring attention to gaps and ethical tensions that warrant more deliberate exploration., Methods: Data sources, Ovid Medline and Cochrane Central Register of Controlled Trials, were searched up to November 2021. Articles included were those in English relating to rGWS deployed rapidly in a critical care setting. Publications were examined for ethical themes and were further characterized as including a superficial or in-depth discussion of that theme. New themes were inductively identified as they emerged., Results: Ninety-nine studies, published in 2012 or thereafter, met inclusion criteria. Themes identified elaborated upon established ethical principles related to beneficence and nonmaleficence (ie, clinical utility, medical uncertainty, impact on family, and data security) autonomy (ie, informed consent), and justice (ie, resource allocation and disability rights). Many themes were only narrowly discussed., Conclusions: The application of rGWS in neonatal and pediatric acute care is inherently tied to ethically charged issues, some of which are reported here. Attention to the ethical costs and benefits of rGWS is not always discussed, with important gaps and unanswered questions that call for ongoing focus on these ethical considerations in this next application of acute care genomics., (Copyright © 2022 by the American Academy of Pediatrics.)