Increasing volume and complexity of cases in academic radiology and the drive toward pediatric sub-specialization have threatened knowledge assimilation for radiologists. There is a clear need for a system that retrieves vetted information from the excess available on the internet. Partnered with an interdisciplinary team from the Graduate School of Education, the authors created the first comprehensive learning management system (LMS) for radiology, implemented in the reading room to augment image interpretation and point-of-care education. The LMS supports quantitative analysis using a robust analytics platform to evaluate user statistics, facilitating improved quality of patient care by revolutionizing the way radiologists assimilate knowledge. This integration promises to enhance workflow and point-of-care teaching and to support the highest quality of care.
Keywords: Analytics; Artificial intelligence; Curriculum development; Education; Learning management system; Process; Radiology.