ArticleJournal of medical ethics2023
Responsibility and decision-making authority in using clinical decision support systems: an empirical-ethical exploration of German prospective professionals' preferences and concerns.
Article in Journal of medical ethics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Physicians' required competencies in AI-assisted clinical settings: a systematic review.British medical bulletin · 2025Pooled it
- Decision support in the management of musculoskeletal disorders: a qualitative study of physiotherapists' and patients' experiences.BMC musculoskeletal disorders · 2026Article
- A Systematic Review of Factors Affecting Utilization of Decision Support Systems: The Interplay Between Technology, Users, and the Healthcare Environment.Health science reports · 2026Review
- Can health technologies be "care optimizers"? A normative evaluation of digital health technologies in light of postphenomenological reflections.Medicine, health care, and philosophy · 2026Article
- Review
- Medical students' and faculty members' perceptions and experiences of AI integration in health care practice and in medical curricula: A meta-ethnographic review.Medical education · 2026Review
- Multidisciplinary perspectives on artificial intelligence in aging research and education: evolving uses, ethics, and equity considerations in gerontology.The Gerontologist · 2026Article
- Job burnout among medical interns: a mixed-methods study of current status, associated factors, and experiential characteristics.Frontiers in psychology · 2026Article
- Hyper-selective explainability: an empirical case study of the utility of explainability in a clinical decision support system.AI and ethics · 2026Article
- Predicting retracted research: a dataset and machine learning approaches.Research integrity and peer review · 2025Article
- Delving into the Practical Applications and Pitfalls of Large Language Models in Medical Education: Narrative Review.Advances in medical education and practice · 2025Review
- Clinicians' roles and necessary levels of understanding in the use of artificial intelligence: A qualitative interview study with German medical students.BMC medical ethics · 2024Article
- [Supporting medical and nursing activities with AI: recommendations for responsible design and use].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2024Article
- Impacts of Clinical Decision Support Systems on the Relationship, Communication, and Shared Decision-Making Between Health Care Professionals and Patients: Multistakeholder Interview Study.Journal of medical Internet research · 2024Article
- Assessing the Utility, Impact, and Adoption Challenges of an Artificial Intelligence-Enabled Prescription Advisory Tool for Type 2 Diabetes Management: Qualitative Study.JMIR human factors · 2024Article
- Physician's autonomy in the face of AI support: walking the ethical tightrope.Frontiers in medicine · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.