ReviewJAMIA open2023
Clinical use of artificial intelligence requires AI-capable organizations.
Review in JAMIA open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Opportunities, challenges, and requirements for Artificial Intelligence (AI) implementation in Primary Health Care (PHC): a systematic review.BMC primary care · 2025Pooled it
- Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial.Journal of the American Medical Informatics Association : JAMIA · 2024Trial
- When Do Physicians Trust AI? The Role of Clinical Context in Decision Support: SMART vignette study.Research square · 2026Article
- Explainability in context: calibrating appropriate trust and reliance in artificial intelligence.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- A Futures Framework for Clinical AI Governance: Anticipating Emerging Risks, Shifting Roles, and Regulatory Challenges.Journal of medical Internet research · 2026Article
- Governance for safe and responsible AI in healthcare organisations: a scoping review of frameworks.NPJ digital medicine · 2026Article
- Artificial Intelligence in Couple and Family Therapy: Introduction of the AI Competencies.Journal of marital and family therapy · 2026Article
- A pre-trained language model approach for triaging surgical patients for preoperative anesthesia clinics.Journal of clinical monitoring and computing · 2026Article
- Performance of 5 AI Models on United States Medical Licensing Examination Step 1 Questions: Comparative Observational Study.JMIR AI · 2026Article
- Important Ethical, Technical, and Epidemiological Considerations in an AI Tool Production (ETEPAI): Scoping Review.JMIR AI · 2026Review
- People, process, technology: a framework for clinical informatics fellowship applicants to evaluate programs.JAMIA open · 2026Review
- NotifAI-OS: an AI framework for automated CT-based opportunistic screening in post-acute value-based care.Nature biomedical engineering · 2025Article
- Artificial intelligence and physician burnout: A productivity paradox.Learning health systems · 2025Article
- Role and Use of Race in Artificial Intelligence and Machine Learning Models Related to Health.Journal of medical Internet research · 2025Article
- Factors Associated With the Accuracy of Large Language Models in Basic Medical Science Examinations: Cross-Sectional Study.JMIR medical education · 2025Article
- Approaches to identify scenarios for data science implementations within healthcare settings: recommendations based on experiences at multiple academic institutions.Frontiers in digital health · 2025Article
- Addressing ethical issues in healthcare artificial intelligence using a lifecycle-informed process.JAMIA open · 2024Article
- ChatGPT vs Expert-Guided Care Pathways for Postesophagectomy Symptom Management.Annals of thoracic surgery short reports · 2024Article
- Preliminary Evidence of the Use of Generative AI in Health Care Clinical Services: Systematic Narrative Review.JMIR medical informatics · 2024Review
- Generative AI in healthcare: an implementation science informed translational path on application, integration and governance.Implementation science : IS · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence-based algorithms are being widely implemented in health care, even as evidence is emerging of bias in their design, problems with implementation, and potential harm to patients. To achieve the promise of using of AI-based tools to improve health, healthcare organizations will need to be AI-capable, with internal and external systems functioning in tandem to ensure the safe, ethical, and effective use of AI-based tools. Ideas are starting to emerge about the organizational routines, competencies, resources, and infrastructures that will be required for safe and effective deployment of AI in health care, but there has been little empirical research. Infrastructures that provide legal and regulatory guidance for managers, clinician competencies for the safe and effective use of AI-based tools, and learner-centric resources such as clear AI documentation and local health ecosystem impact reviews can help drive continuous improvement.
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.