ArticleJournal of medical ethics2024
Clinicians and AI use: where is the professional guidance?
Article in Journal of medical ethics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 3 of them syntheses 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
23 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Trust in Artificial Intelligence-Based Clinical Decision Support Systems Among Health Care Workers: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Physicians' required competencies in AI-assisted clinical settings: a systematic review.British medical bulletin · 2025Pooled it
- Predictors of Health Care Practitioners' Intention to Use AI-Enabled Clinical Decision Support Systems: Meta-Analysis Based on the Unified Theory of Acceptance and Use of Technology.Journal of medical Internet research · 2024Pooled it
- Nursing Professional Organisations as Human Rights Intermediaries: Towards an Integrated Framework of Stakeholdership for Healthcare AI Governance.Journal of clinical nursing · 2026Review
- Perceptions, knowledge and adoption of artificial intelligence in rheumatology: results from a British Society for Rheumatology survey.Rheumatology (Oxford, England) · 2026Article
- Effects of Type and Timing of Clinician-Facing AI Support on Patient Trust in Medical Consultations: 2 Vignette Experiments.Journal of medical Internet research · 2026Article
- The Risks to Patients Associated with Using Artificial Intelligence Tools in Pharmacy Practice: A Scoping Review.Pharmacy (Basel, Switzerland) · 2026Review
- Principles for Responsible AI in Health Professions Education, Research, and Care: Health CARE-AI (Contextual, Accountable, Responsible, and Equitable Artificial Intelligence) Framework Delphi Consensus Study.JMIR medical education · 2026Article
- Understanding Clinicians' Informational Needs for AI-Driven Clinical Decision Support Systems: Qualitative Interview Study.JMIR medical education · 2026Article
- The unintended negative consequences of artificial intelligence use for psychologists.Frontiers in psychology · 2026Article
- Developing professional ethical guidance for healthcare AI use (PEG-AI): an attitudinal survey pilot.AI & society · 2025Article
- Clinical obstacles to machine-learning POCUS adoption and system-wide AI implementation (The COMPASS-AI survey).The ultrasound journal · 2025Article
- Generalizability, robustness, and correction bias of segmentations of thoracic organs at risk in CT images.European radiology · 2025Article
- Ethical aspects of artificial intelligence: what urologists need to know.Current opinion in urology · 2025Review
- Article
- Regulating professional ethics in a context of technological change.BMC medical ethics · 2024Article
- Generative artificial intelligence in ophthalmology: current innovations, future applications and challenges.The British journal of ophthalmology · 2024Review
- Accidental injustice: Healthcare AI legal responsibility must be prospectively planned prior to its adoption.Future healthcare journal · 2024Article
- Using Artificial Intelligence in Patient Care-Some Considerations for Doctors and Medical Regulators.Asian bioethics review · 2024Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
With the introduction of artificial intelligence (AI) to healthcare, there is also a need for professional guidance to support its use. New (2022) reports from National Health Service AI Lab & Health Education England focus on healthcare workers' understanding and confidence in AI clinical decision support systems (AI-CDDSs), and are concerned with developing trust in, and the trustworthiness of these systems. While they offer guidance to aid developers and purchasers of such systems, they offer little specific guidance for the clinical users who will be required to use them in patient care.This paper argues that clinical, professional and reputational safety will be risked if this deficit of professional guidance for clinical users of AI-CDDSs is not redressed. We argue it is not enough to develop training for clinical users without first establishing professional guidance regarding the rights and expectations of clinical users.We conclude with a call to action for clinical regulators: to unite to draft guidance for users of AI-CDDS that helps manage clinical, professional and reputational risks. We further suggest that this exercise offers an opportunity to address fundamental issues in the use of AI-CDDSs; regarding, for example, the fair burden of responsibility for outcomes.
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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.