AI Insight
This study conducted a retrospective economic costing analysis examining the healthcare resources required to evaluate, deploy, and monitor an AI-based reconstruction system for rectal MRI examinations within the NHS. The AI reconstruction reduced scan duration by 22 minutes, generating theoretical monthly savings of approximately 3,437 pounds, reduced to around 2,541 to 2,636 pounds when ongoing quality control measures were included. The initial clinical evaluation cost of approximately 15,023 pounds was estimated to be recouped within 4.4 to 6 months depending on the quality control approach adopted.
Why it matters
This research provides a practical financial framework for healthcare systems considering AI-based imaging tools, demonstrating that automated image quality metrics for post-deployment monitoring are more cost-effective than repeated radiologist scoring, which has direct implications for how hospitals plan AI integration budgets and workflows.
⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
Objectives: AI-based reconstructions can reduce MRI acquisition times and/or improve image quality. Guidelines recommend clinical evaluations and post-deployment monitoring of these novel methods, however, there has been little investigation of the clinical resources required for such assessments. The aim of this study was to evaluate the healthcare resource utilisation and potential savings associated with AI-based reconstructions in rectal MRI. Methods: A retrospective economic costing analysis was conducted from the NHS healthcare perspective. Resource utilisation data were extracted from the Electronic Patient Records for 9 healthy volunteer scans and 104 rectal MRI examinations evaluating an AI-based reconstruction. The resource profile included the MRI scan and the staff time required for data acquisition and analysis. Results: The clinical evaluation of the AI-based reconstruction cost {pound}15,023. Deployment of the AI-based reconstruction reduced the length of an MRI rectum scan by 22 minutes, theoretically saving approximately {pound}3,437 per month. Addition of post-deployment quality control scans reduced this monthly saving to {pound}2,636. If the quality control scans were evaluated using radiologists rather than image quality metrics, monthly savings would be approximately {pound}2,541. With ongoing quality control, the clinical evaluation cost would be recouped between 5.8 and 6 months, compared with 4.4 months without ongoing quality control. Conclusions: Deploying AI-based reconstructions can yield cost savings through reduced scanning times. Quality control tests using image quality metrics would save radiological burden and reduce costs compared with conducting repeated image scoring by radiologists.