Artificial Intelligence in UK Hospital Medicine: From Innovation to Implementation

Artificial Intelligence (AI) has the potential to enhance patient care in the UK's increasingly pressured healthcare system. As AI's applications in healthcare are expanding, healthcare professionals should understand the processes underpinning how AI tools translate from research to clinical application. There are several stages: (1) training and validation on healthcare data, (2) generation of evidence demonstrating performance and safety, (3) regulatory compliance, (4) AI product procurement, (5) implementation in clinical settings, and (6) ongoing monitoring and oversight of deployed AI. Each step presents unique challenges and opportunities that can influence successful integration. Clinicians should understand AI's capabilities and limitations to ensure its appropriate and effective use in practice. This review aims to provide a structured overview of the AI adoption pathway in healthcare, with a view to supporting clinicians in critically appraising its potential and limitations, optimising its integration into clinical practice, and engaging with AI in an informed manner.

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Publication Details

Journal
British Journal of Hospital Medicine
Published
2025-12-19
DOI
https://doi.org/10.12968/hmed.2025.0468
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence in UK Hospital Medicine: From Innovation to Implementation

Vijna Boodhoo, David Lowe, C Carlin, David Carroll
British Journal of Hospital Medicine
Artificial Intelligence in Healthcare and Education
article

Artificial Intelligence in UK Hospital Medicine: From Innovation to Implementation

Vijna Boodhoo, David Lowe, C Carlin, David Carroll
article en

Abstract

Artificial Intelligence (AI) has the potential to enhance patient care in the UK's increasingly pressured healthcare system. As AI's applications in healthcare are expanding, healthcare professionals should understand the processes underpinning how AI tools translate from research to clinical application. There are several stages: (1) training and validation on healthcare data, (2) generation of evidence demonstrating performance and safety, (3) regulatory compliance, (4) AI product procurement, (5) implementation in clinical settings, and (6) ongoing monitoring and oversight of deployed AI. Each step presents unique challenges and opportunities that can influence successful integration. Clinicians should understand AI's capabilities and limitations to ensure its appropriate and effective use in practice. This review aims to provide a structured overview of the AI adoption pathway in healthcare, with a view to supporting clinicians in critically appraising its potential and limitations, optimising its integration into clinical practice, and engaging with AI in an informed manner.

British Journal of Hospital MedicineVol. 86(12)
Queen Elizabeth University Hospital (GB), University of Glasgow (GB)
Openalex Percentile: Top 64%
Artificial Intelligence in Healthcare and Education
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Artificial Intelligence in UK Hospital Medicine: From Innovation to Implementation — Vijna Boodhoo, David Lowe, et al. · British Journal of Hospital Medicine (2025) | TGRS Research Map | TGRS