ArticleHealthcare informatics research2023
Healthcare Professionals' Expectations of Medical Artificial Intelligence and Strategies for its Clinical Implementation: A Qualitative Study.
Article in Healthcare informatics research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
What it found
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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.
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Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 28 citations in OpenAlex.
- Healthcare Professionals' Perceptions of Artificial Intelligence in Healthcare-A Systematic Review of Qualitative Studies.Journal of advanced nursing · 2026Pooled it
- Improving Explainability and Integrability of Medical AI to Promote Health Care Professional Acceptance and Use: Mixed Systematic Review.Journal of medical Internet research · 2025Pooled it
- Attitudes, Needs, and Expectations Regarding the Application of AI in Occupational Healthcare: A Multiple Stakeholder Perspective.Journal of occupational and environmental medicine · 2026Article
- Is accuracy enough? trust and barriers to AI-based clinical decision support in clinical neurophysiology.Clinical neurophysiology practice · 2026Article
- An Investigation Into the Comprehension, Perceptions, Application, and Determinants Affecting the Utilization of Deepseek Artificial Intelligence by Healthcare Professionals: A Cross-Sectional Study.Health science reports · 2025Article
- Physicians' perceptions and attitudes on artificial intelligence in hospital management: a qualitative study.BMC health services research · 2025Article
- Artificial intelligence in nursing practice: a qualitative study of nurses' perspectives on opportunities, challenges, and ethical implications.BMC nursing · 2025Article
- Nursing students metaphorical perceptions of the concept of "Artificial intelligence" and their views on the future of artificial intelligence.BMC nursing · 2025Article
- Comparison of SHAP and clinician friendly explanations reveals effects on clinical decision behaviour.NPJ digital medicine · 2025Article
- Knowledge, attitudes, and practices of cardiovascular health care personnel regarding coronary CTA and AI-assisted diagnosis: a cross-sectional study.Journal of global health · 2025Article
- Health Care Professionals' Concerns About Medical AI and Psychological Barriers and Strategies for Successful Implementation: Scoping Review.Journal of medical Internet research · 2025Article
- Bias recognition and mitigation strategies in artificial intelligence healthcare applications.NPJ digital medicine · 2025Review
- Artificial Intelligence in Chronic Disease Management for Aging Populations: A Systematic Review of Machine Learning and NLP Applications.International journal of general medicine · 2025Review
- Exploring the perspectives of healthcare professionals regarding artificial intelligence; acceptance and challenges.BMC health services research · 2024Article
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- Closing the Gap in VTE Prophylaxis: The Role of Clinical Decision Support.JACC. Advances · 2023Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesAlthough medical artificial intelligence (AI) systems that assist healthcare professionals in critical care settings are expected to improve healthcare, skepticism exists regarding whether their potential has been fully actualized. Therefore, we aimed to conduct a qualitative study with physicians and nurses to understand their needs, expectations, and concerns regarding medical AI; explore their expected responses to recommendations by medical AI that contradicted their judgments; and derive strategies to implement medical AI in practice successfully.
methodsSemi-structured interviews were conducted with 15 healthcare professionals working in the emergency room and intensive care unit in a tertiary teaching hospital in Seoul. The data were interpreted using summative content analysis. In total, 26 medical AI topics were extracted from the interviews. Eight were related to treatment recommendation, seven were related to diagnosis prediction, and seven were related to process improvement.
resultsWhile the participants expressed expectations that medical AI could enhance their patients' outcomes, increase work efficiency, and reduce hospital operating costs, they also mentioned concerns regarding distortions in the workflow, deskilling, alert fatigue, and unsophisticated algorithms. If medical AI decisions contradicted their judgment, most participants would consult other medical staff and thereafter reconsider their initial judgment.
conclusionsHealthcare professionals wanted to use medical AI in practice and emphasized that artificial intelligence systems should be trustworthy from the standpoint of healthcare professionals. They also highlighted the importance of alert fatigue management and the integration of AI systems into the workflow.
Indexed as
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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.