Governance for safe and responsible AI in healthcare organisations: a scoping review of frameworks.
systematic_review · Level I
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- Record sourced from PubMed, PMID 42062453.
- Also identified by DOI 10.1038/s41746-026-02679-2.
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Abstract
This scoping review synthesises current evidence on artificial intelligence (AI) governance in healthcare organisations, outlining key components of AI governance frameworks. Following PRISMA-ScR guidelines, we searched MEDLINE, Embase, and Scopus (April 2024, updated March 2025) for AI governance frameworks in acute care. Seventy-seven frameworks were identified and examined for four components: (1) Guiding principles (ethics or governance-related); (2) Assessment methods; (3) AI lifecycle stages; and (4) Oversight mechanisms. Most frameworks were not applicable to real-world healthcare settings and missed key principles or components, such as an oversight mechanism. Only 10 frameworks (13.0%) included all four framework components, with oversight mechanisms (e.g. AI-specific governance committee) being the least common (n = 15, 19.5%). There is a need to move beyond principles to implementing AI governance frameworks in healthcare organisations and evaluating their real-world impact.