A UCL-led study identifies significant challenges in deploying AI tools for chest diagnostics across NHS hospitals in England.
Key Details
- 1The study analysed procurement and deployment of AI chest diagnostic tools (X-ray/CT) in 66 NHS hospital trusts.
- 2Delays were significant: by June 2025, one-third of trusts (23/66) had not yet implemented the tools clinically, 18 months after planned completion.
- 3Key hurdles included complex governance, lengthy contracts (4–10 months longer than expected), staff workload, outdated IT systems, and clinician skepticism toward AI.
- 4Enablers included strong national leadership, local network collaboration, and dedicated project management.
- 5The study recommends more targeted staff training and ongoing project management support for future AI rollouts.
Why It Matters
This study provides real-world evidence of the operational, technical, and human challenges faced in scaling AI for radiology in major health systems. Understanding these obstacles is crucial for radiology departments, policymakers, and technology vendors aiming to translate AI from pilot projects into routine clinical practice.
Source
EurekAlert
Related News
•EurekAlert
AI Pathology Tool SÉMIL Improves Stage II Bowel Cancer Risk Assessment
A La Trobe University-developed AI tool accurately predicts relapse risk in stage II bowel cancer using digital pathology images and descriptions.
•EurekAlert
AI-Guided Handheld Cardiac Ultrasound Reduces Referrals and Costs in Spain
AI-guided handheld cardiac ultrasound enables primary care physicians to detect heart failure, reducing specialist referrals and saving costs.
•EurekAlert
AI Tool Predicts Which Rectal Cancer Patients Benefit from Intensive Therapy
UCL researchers developed an AI that analyzes biopsy slides to identify rectal cancer patients who benefit from adding irinotecan to standard chemoradiotherapy.