Evidence-based medicine (EBM) has been defined as the process of systematically finding, appraising, and incorporating contemporary research findings into clinical decision making. The concept and name were first formally introduced by Gordon Guyatt1 and colleagues from the McMaster University in Ontario, Canada, in 1991. The principle goal of EBM is to provide a conscientious scientific basis for clinical decision making. In doing so, EBM serves as a methodological strategy to streamline and objectify the decision-making process. EBM serves to integrate clinical experience with the best available scientific data, available through the peer-reviewed scientific literature, databases, and clinical trials. The pooled data and knowledge offered through medical informatics and its supporting technologies provide the infrastructure to facilitate evidence-based radiology (EBR), which, in theory, leads to improved clinical outcomes. In its present form, however, EBR focuses almost exclusively on the radiology report and imaging diagnosis. By doing so, however, many of the essential steps in the imaging chain are largely ignored––steps that ultimately affect the quality of imaging services and clinical outcomes. Examples of some of these quality indicators, and the corresponding steps and technologies are listed in Table 1. Table 1 Quality Indicators throughout the Imaging Chain These individual, stepwise, quality-oriented metrics form the collective basis of outcomes analysis within radiology by acknowledging that the collective radiology product is a sum total of multiple steps, performed by multiple individuals, using multiple technologies. The various data elements attributed to each individual step in the collective imaging chain create the ability to use medical informatics to objectively analyze performance deliverables and differentiate medical imaging service providers in data-driven qualitative and quantitative terms. This data-driven, quality-oriented analysis is crucial to the long-term survival of medical imaging, where the trend toward commoditization is accelerating because of globalization, increased information exchange, and technological developments.2 The same evolutionary technology forces that have improved radiology productivity and workflow have also accentuated this commoditization trend through the widespread adoption of teleradiology and universal information technology (IT) standards (such as HL-7, IHE, and DICOM). When products or services are perceived to be supplied equally well by multiple providers, then those products or services become a commodity, and price becomes the driving factor in determining supplier selection. This is slowly becoming a reality within the population of medical imaging consumers. Qualitative differentiation is the best solution to avoid commoditization, so that the service offering is distinguished from that of competitors through enhanced performance measures (i.e., added value service).3 Technology has improved operational efficiency within radiology practice and has also facilitated access to imaging studies by radiologists who are located outside the local healthcare environment. The widespread use of teleradiology for primary or secondary interpretation has become a contributing factor toward the perception of a lack of difference in quality of care among different radiology providers. This has resulted in acceptance of commoditization in diagnostic imaging, which has, in turn, made it more difficult for groups that provide higher quality service to successfully compete for contracts. Medical informatics provides the mechanism to track, store, analyze, and report quality performance indicators intrinsic to radiology practice, thereby providing an objective mechanism for providers to differentiate themselves based on quality metrics.