ArticleRisk management and healthcare policy2024
Managing Risk and Quality of AI in Healthcare: Are Hospitals Ready for Implementation?
Article in Risk management and healthcare policy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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Who cites it
9 citing papers in PubMed.
- Review
- Evaluation Strategies for Large Language Model-Based Models in Exercise and Health Coaching: Scoping Review.Journal of medical Internet research · 2025Article
- Attitudes and readiness to adopt artificial intelligence among healthcare practitioners in Pakistan's resource-limited settings.BMC health services research · 2025Article
- Learning health system strategies in the AI era.npj health systems · 2025Review
- Guiding responsible AI in healthcare in the Philippines.NPJ digital medicine · 2025Review
- Artificial intelligence in emergency department triage: perspective of human professionals.Frontiers in digital health · 2025Article
- Building a healthcare data warehouse: considerations, opportunities, and challenges.Frontiers in digital health · 2025Review
- Preparing hospitals and health organizations for AI: practical guidelines for the required infrastructure.Frontiers in digital health · 2025Article
- Revolutionising oral organoids with artificial intelligence.Biomaterials translational · 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 (AI) provides a unique opportunity to help meet the demands of the future healthcare system. However, hospitals may not be well equipped to handle safe and effective development and/or procurement of AI systems. Furthermore, upcoming regulations such as the EU AI Act may enforce the need to establish new management systems, quality assurance and control mechanisms, novel to healthcare organizations. This paper discusses challenges in AI implementation, particularly potential gaps in current management systems (MS), by reviewing the harmonized standard for AI MS, ISO 42001, as part of a gap analysis of a tertiary acute hospital with ongoing AI activities. Examination of the industry agnostic ISO 42001 reveals a technical debt within healthcare, aligning with previous research on digitalization and AI implementation. To successfully implement AI with quality assurance in mind, emphasis should be put on the foundation and structure of the healthcare organizations, including both workforce and data infrastructure.
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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.