Boneview-ED Impact of Artificial Intelligence on Fracture Detection in Emergency Department A Pragmatic Prospective Study

What this Trial Is About

Traumatic injuries are a common reason for emergency department visits, and standard X-rays are the main imaging method used to detect bone fractures. However, with the increasing number of patients, emergency staff face challenges in accurately interpreting these images, leading to a higher risk of missed fractures. Researchers are evaluating the use of artificial intelligence (AI) software called "Boneview" to help emergency physicians detect fractures more accurately during their routine work in a real emergency care setting. In this study, after patients receive an X-ray for suspected bone injury, the senior emergency physician first reviews the images without AI assistance and records their diagnosis and decisions about specialist referrals. Then, the same images are processed by the Boneview AI software, and the physician re-evaluates the images considering the AI analysis, updating their diagnosis and management plan as needed. A radiology intern and a specialized radiologist will also read the X-rays twice—first without AI and then with AI assistance—to compare results. This approach aims to see how AI impacts diagnosis and patient care in the emergency department. Participants will receive no extra imaging beyond their standard X-rays, but their X-rays will be reviewed again with AI support to check for any differences in diagnosis. If there is a disagreement between the initial readings and the specialized radiologist's reading, patients may be contacted for further evaluation. The study will measure the changes in emergency room support decisions made with and without AI over one year, tracking how AI influences patient management and care outcomes during their emergency visit.

Boneview-ED - Impact of Artificial Intelligence Detecting Fractures in the Emergence Department : a Pragmatic Prospective Study