Responsibility and decision-making authority in using clinical decision support systems: an empirical-ethical exploration of German prospective professionals’ preferences and concerns

Machine learning-driven clinical decision support systems (ML-CDSSs) seem impressively promising for future routine and emergency care. However, reflection on their clinical implementation reveals a wide array of ethical challenges. The preferences, concerns and expectations of professional stakehol...

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Bibliographic Details
Published in:Journal of medical ethics 2024-01, Vol.50 (1), p.6-11
Main Authors: Funer, Florian, Liedtke, Wenke, Tinnemeyer, Sara, Klausen, Andrea Diana, Schneider, Diana, Zacharias, Helena U, Langanke, Martin, Salloch, Sabine
Format: Article
Language:English
Subjects:
Artificial intelligence
Attitude of Health Personnel
Clinical decision making
Clinical Ethics
Data analysis
Data collection
Decision Making
Decision support systems
Decision Support Systems, Clinical
Empirical Research
Ethics
Ethics- Medical
Group Processes
Health Personnel
Humans
Information Technology
Interviews
Long term health care
Medical students
Nephrology
Nursing
Professional ethics
Professionals
Prospective Studies
Qualitative Research
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Summary:Machine learning-driven clinical decision support systems (ML-CDSSs) seem impressively promising for future routine and emergency care. However, reflection on their clinical implementation reveals a wide array of ethical challenges. The preferences, concerns and expectations of professional stakeholders remain largely unexplored. Empirical research, however, may help to clarify the conceptual debate and its aspects in terms of their relevance for clinical practice. This study explores, from an ethical point of view, future healthcare professionals’ attitudes to potential changes of responsibility and decision-making authority when using ML-CDSS. Twenty-seven semistructured interviews were conducted with German medical students and nursing trainees. The data were analysed based on qualitative content analysis according to Kuckartz. Interviewees’ reflections are presented under three themes the interviewees describe as closely related: (self-)attribution of responsibility, decision-making authority and need of (professional) experience. The results illustrate the conceptual interconnectedness of professional responsibility and its structural and epistemic preconditions to be able to fulfil clinicians’ responsibility in a meaningful manner. The study also sheds light on the four relata of responsibility understood as a relational concept. The article closes with concrete suggestions for the ethically sound clinical implementation of ML-CDSS.
ISSN:0306-6800
1473-4257
DOI:10.1136/jme-2022-108814