Systematic Assessment of the Medical Utility of Radiology Artificial Intelligence (SAMURAI) in Fracture Detection
Patients undergoing X-ray for suspected fracture in the emergency department or minor injuries unit
The trial will involve installing a MHRA- and CE-approved AI fracture detection software at each site for 6 months. Clinicians will be able to view AI annotated images to aid in diagnosis when reviewing X-rays for suspected fracture. Sites will be randomly assigned to begin the trial with the AI algorithm either active ("On") or inactive ("Off") during the first month. Thereafter, the algorithm status will alternate each month (“AI On” and “AI Off”) for the remaining 5 months. This crossover design ensures that each site experiences both conditions multiple times, allowing within-site comparisons of outcomes under AI-assisted versus standard practice. This study will be conducted across four sites, divided into three clusters: Cluster 1: Oxford University Hospitals NHS Foundation Trust: John Radcliffe Hospital ED (Level 1 ED) Horton General Hospital ED (Level 1 ED) Oxford Health Trust: MIUs (Level 3 EDs) Cluster 2: Royal Berkshire NHS Foundation Trust: Royal Berkshire Hospital ED (Level 1 ED) Associated MIUs (Level 3 ED) Cluster 3: Buckinghamshire Healthcare NHS Trust: Stoke Mandeville Hospital ED (Level 1 ED) Associated MIUs (Level 3 ED) All patients undergoing an X-ray for suspected fracture will be eligible for the study. Dedicated research teams at each site will extract data from Electronic Patient Records and share the anonymised data with the central trial team for evaluation of primary and secondary outcomes. We will gather feedback from patients and clinical staff through electronic surveys at each site. These sites will allow for sufficient patient heterogeneity (socioeconomic, geographical, population, ethnicity) as per the INCLUDE guidance to ensure that our results are generalisable to the wider UK population.
All patients undergoing X-Rays in ED or MIU for a suspected fracture will be eligible for inclusion
1. Patients under 2 years old 2. Skeletal survey conducted to assess for non-accidental injury 3. Skull, facial bone, dental, and cervical spine X-rays 4. Thoracolumbar spine X-rays in patients under 18 years old 5. Patient has opted out of data sharing on the National Data Opt-Out 6. Patient completes the opt out questionnaire displayed on posters in the waiting room