In the Journal of the American College of Radiology: JACR, Reiner and Siegel¹ recommended 12 measures that could reduce the commoditization of radiology.
The first step is the refinement of the terminology related to quality assurance (QA) in the RadLex® lexicon, including improvement of terms and definitions and their relative relationships, as well as a development of a quantitative set of terms for describing and measuring QA deficiencies.
The second is the creation of an imaging-community model for both qualitative and quantitative QA analysis that would include standards for quality in descriptive terms and reference images to help achieve consensus on quality.
The third is the creation of funding mechanisms to encourage research and educational grants that focus on medical-imaging QA and corresponding improvements in patient safety and clinical outcomes.
The fourth is collaboration among governmental agencies (for example, CMS, the National Institute of Standards and Technology, and the National Institutes of Health) and medical-imaging technology vendors and their associations (such as NEMA) to improve existing technical solutions and to develop new QA-related approaches.
The fifth is the definition of both technical and clinical QA standards to serve as industry-wide models for QA technology development.
The sixth is the augmentation of subjective QA methodologies with objective and reproducible QA metrics that can help transcend individual perceptions and biases.
The seventh is the development of universal QA databases that are both institution neutral and vendor neutral, and that can automate the collection, analysis, and storage of QA data for external review and analysis.
The eighth is the acceleration of pay-for-performance economic incentives by third-party payors to promote proactive QA in everyday medical-imaging practice.
The ninth is public dissemination of objective quality metrics to the consuming public (through the Internet, for instance) to facilitate informed decision making in the selection of medical-imaging services.
The tenth is the development of clinician, radiologist, and technologist review processes and computer-aided analytic algorithms to improve the consistency of assessment of image quality, diagnostic accuracy, and examination appropriateness using an informatics-based approach.
The eleventh is the creation of a standard for reporting these objective QA measurements and of a means for reporting them, combining data from multiple disparate information systems within an imaging department and hospital enterprise that would allow benchmarking of quality information for imaging practices.
The twelfth step is the creation of a culture that encourages QA and quality improvement in a positive and constructive manner, as suggested for reporting hospitals’ medical errors.