Data-Driven Quality and Safety Programs in Radiology

Health care today is transitioning from a volume-based, fee-for-service model to a qualityand value-oriented model.^1,2 This transition is forming intricate, wide-reaching quality agendas and infrastructures that are used to track quality measures. Quality targets are chosen carefully and prioritized. A large number of metrics are tied to fair market value; they are chosen to measure individual and collective progress in meeting quality standards, trends in imaging use, and radiologist effectiveness. Examples of these fair-market-value metrics range from appropriateness of imaging orders from the referring provider and effective use of a new ordering interface to protocol optimization.^1,3