ArticleJournal of the American College of Emergency Physicians open2026
Artificial Intelligence Readiness in Emergency Medicine: Expert Consensus Opinion for Preparing the Workforce.
Article in Journal of the American College of Emergency Physicians open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid integration of artificial intelligence (AI) into emergency department workflows has outpaced clinician training, vendor evaluation infrastructure, and specialty-wide governance. Emergency physicians increasingly encounter AI tools spanning triage, imaging, clinical decision support, documentation, and operations, yet most lack the foundational skills to critically evaluate or safely oversee these products. Without a unified framework, departments struggle to distinguish safe tools from risky ones, and no national standard exists to guide education, vetting, or implementation. This expert consensus opinion, an official work product of the American College of Emergency Physicians (ACEP) AI Task Force formally endorsed by the ACEP Board of Directors in 2025, proposes 3 coordinated priorities to address these gaps. Educate: outlines a standardized AI education framework spanning residency training through continuing medical education, anchored in existing specialty-specific competencies. Evaluate: proposes an expert-derived, structured, clinician-led three-stage framework for vetting AI tools and industry partners prior to deployment. Advise: calls for the establishment of a national Emergency Medicine AI Advisory Council to issue shared terminology, best-practice guidance, and implementation toolkits across academic, community, and critical access settings. Together, these recommendations provide an adaptable, expert-derived foundation for ensuring that AI integration in emergency medicine is safe, equitable, and clinically effective.
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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.