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Although the potential for adverse clinical outcomes related to medical radiation have been well documented for over a century, several relatively recent trends have increased awareness of radiation safety in medical imaging. These include expanded CT applications and utilization, increased patient attention on radiation carcinogenesis, and a wide array of legislative and societal radiation initiatives, created partly in response to media reports of CT-induced radiation complications. With this heightened radiation awareness and scrutiny comes a unique and timely opportunity for the collective medical-imaging community to incorporate comparative radiation metrics and analysis directly into routine workflow and reporting. If properly performed, a number of benefits could in theory be derived, including improved clinical outcomes, creation of data-driven best practice guidelines, opportunities for enhanced education and research, dose-reduction technology innovation, and reversal of existing commoditization trends. [ABSTRACT FROM AUTHOR]

Although image quality is a well-recognized component in the successful delivery of medical imaging services, it has arguably declined over the past decade owing to several technical, economic, cultural, and geographic factors. To improve quality, the radiologist community must take a more proactive role in image quality analysis and optimization; these require analysis of not just the single step of image acquisition but the entire imaging chain. Radiologists can benefit through improved report accuracy, diagnostic confidence, and workflow efficiency. The derived data-driven analyses offer an objective means for provider performance analysis, which can help combat commoditization trends and self-referral by nonradiologist providers. [ABSTRACT FROM AUTHOR]

An accurate clinical assessment of how radiology report data affect health care outcomes cannot be performed without the standardization, integration, and longitudinal analysis of radiology report and clinical outcomes data. The creation of such a technology can be accomplished by creating a standardized finding-specific radiology and clinical database, in which individual report findings are assigned extensible markup language tags and tracked over time with associated clinical data. The derived knowledge can in turn be used to improve overall outcomes through the data-derived analysis of reporting accuracy, imaging utilization, the timeliness of clinical care, and compliance with best practice guidelines. [Copyright &y& Elsevier]

Correlation of historical imaging and radiology report data with the current imaging data set is a critical step in the radiologic interpretation process and, if incomplete, can adversely affect diagnostic accuracy. In its current form, the extraction and analysis of historical imaging and report data is limited by manual workflow, inefficient data organization, and a lack of imaging and report data integration. The reconciliation of historical and contemporaneous radiology report data provides an opportunity to improve the consistency, completeness, and accuracy of radiology report data, while providing opportunities to automate workflow related to data extraction, interpretation, and peer review. The derived data analytics can in turn be used to facilitate physician consultations, education and training, and proactive intervention in the event of report discrepancies. [ABSTRACT FROM AUTHOR]

Data reconciliation in medical imaging is designed to ensure the accuracy and integrity of data across multiple steps in the imaging cycle, ultimately leading to improved continuity of patient care. An integral component of this data reconciliation is tied to the steps of clinical order entry and radiology report creation. The clinical data presented at order entry by the referring clinician influence a number of important imaging decisions, including examination selection, protocol design, image acquisition and processing, and interpretation of the imaging data set. The subsequent data derived from the radiology report have a profound impact on diagnosis, treatment, and overall clinical management. As a result, the reconciliation of clinical order entry and radiology report data affect health care delivery and in many respects are dependent on each other for optimal outcomes. The creation of a standardized reconciliation database that proactively records, tracks, analyzes, and provides feedback to radiologists and clinicians offers the potential to improve the quality and efficiency of patient care, while providing objective accountability measures for individual and institutional health care providers. [ABSTRACT FROM AUTHOR]

The concept of data reconciliation has been well described in the industrial and pharmaceutical literature and is designed to ensure the integrity, reliability, and accuracy of sequential data in a multistep process. This concept can similarly be applied to the delivery of medical imaging services, which begins with order entry and ends with reporting and communication. The ultimate goal of medical imaging data reconciliation is to ensure continuity of care, extending across multiple service providers and imaging and information system technologies. The longitudinal analysis of standardized data across the imaging continuum presents an opportunity to improve communication between service providers, education and training, workflow, and clinical outcomes. In addition, the derived data can in turn be used to create data-driven best-practice guidelines and computerized decision support tools. [Copyright &y& Elsevier]

The Institute of Medicine has determined that adverse drug events (ADEs) are the number one cause of medical errors in the United States and that additional efforts are required to improve patient safety. Medical imaging plays an important role in ADEs, most commonly related to the administration of imaging contrast agents. For medical imaging providers to assume a proactive role in patient safety, the creation of objective, data-driven quality metrics is advocated, which analyze all steps in the drug delivery chain, including procurement, prescription, dispersal, administration, monitoring, and management. These metrics would lead to the creation of a quality scorecard, developed to create objective accountability measures for all actors involved in this chain of events, including pharmacists, radiologists, clinicians, physicists, technologists, administrators, nurses, vendors, and patients. The ultimate goal of such an endeavor is to improve patient safety through the reduction of ADEs and the creation and refinement of data-driven best-practice guidelines. [Copyright &y& Elsevier]

The practice of medical imaging is fraught with inconsistency as it relates to quality assurance, which is due in part to the lack of standardization and objective quality-centric data. By applying the scientific methods of Shewhart and Deming to medical imaging quality assessment, one can devise an objective, data-driven quality model, encompassing the various steps and processes that take place within the medical imaging chain. Through automated recording, tracking, and analysis of these quality data elements, a quantitative scorecard can be derived that provides an objective measure of quality performance, relating to each individual process, participating stakeholder, and technology being used. Through meta-analysis of these quality-centric data, best practice guidelines can be created, which in turn promote quality as the major differentiating feature of service providers. [Copyright &y& Elsevier]

As the utilization of medical imaging services continues to expand, so does the delivery of ionizing radiation. Although recent efforts within the medical imaging community have begun to focus on radiation dose reduction for computed tomography, very few objective data related to radiation dose are currently being prospectively collected, tracked, or analyzed. Without a comprehensive program aimed at objective and reproducible radiation data analysis, ongoing efforts at dose optimization will, in all likelihood, remain marginalized. The proposed radiation scorecard provides an analysis of events within the imaging chain, attempts to involve all stakeholders, and addresses the various technologies being utilized. The combined data can in turn be used for education and training, certification, research, development of best practice guidelines, and new technology development. [Copyright &y& Elsevier]

An integral part of cost-benefit analysis within medicine is the comparative assessment of the clinical gains introduced by a service or application compared with the patient costs, which can be measured in economic or clinical terms. When analyzing medical imaging, a number of factors must be included, the most important of which include issues pertaining to patient safety, image quality, and clinical outcomes. Although ionizing radiation has long been recognized as a potential carcinogen capable of introducing harm to patients, the long-term derived benefits have been accepted because of the diagnostic and therapeutic benefits derived from its use. With the increased utilization of high-dose ionizing radiation examinations (such as multidetector computed tomography), it is essential that the medical community create data-driven methodologies to quantify risk in objective terms, develop community-wide radiation standards and “best practice” guidelines (evidence-based medicine), develop new technologies and applications to proactively minimize radiation dose while maintaining quality, and create accountability measures for all pertinent stakeholders. [Copyright &y& Elsevier]

The existing practice of quality assurance (QA) in medical imaging is problematic because of the subjective manner in which it is performed, the lack of community and industry-wide QA standards, a paucity of supporting technology, and an overall lack of accountability. The solution for optimizing QA lies in the creation of objective and reproducible QA metrics, whose analysis can be automated through the creation of computerized QA software algorithms. The QA data derived from these computerized programs would in turn create the infrastructure for a comprehensive QA database, which can serve as a valuable resource for QA education and training, research, decision support, and technology innovation. The ability to objectively track and analyze QA practice across the wide spectrum of imaging providers creates a mechanism for the creation and refinement of objective QA standards and “best practice” guidelines. [Copyright &y& Elsevier]

The current focus on the economic bottom line in health care creates the potential for radiology to become a commodity, devoid of qualitative differentiation. This trend toward commoditization has been accelerated by the globalization of imaging services (teleradiology), increased information exchange (eg, Digital Imaging and Communications in Medicine, Integrating the Healthcare Enterprise), and new technology development (eg, picture archiving and communication systems, computer-aided diagnosis). The optimum strategy for avoiding commoditization is the creation of objective quality metrics and standards throughout the medical imaging practice, which will provide a reproducible and objective means with which to differentiate imaging service deliverables on the basis of quality and clinical outcomes. These quality measures can in turn be directly tied to economic incentives (pay for performance), providing further incentive for proactive quality assurance, qualitative differentiation, and technology development centered on quality. [Copyright &y& Elsevier]

Although imaging technologies have undergone dramatic evolution over the past century, radiology reporting has remained largely static, in both content and structure. Existing free-text (prose) reports have been criticized for a number of inherent deficiencies, including inconsistencies in content, structure, organization, and nomenclature. A number of new initiatives and technologies now present the radiology community with the unique opportunity to fundamentally change the radiology report from free to structured text. These new developments include a standardized nomenclature (RadLex), automated information technologies (picture archiving and communications systems and electronic medical records), and automated data tracking and analysis software (natural-language processing). Despite the increasing availability of these tools and technologies for revolutionizing reporting, clinical, psychologic, legal, and economic challenges have collectively limited structured reporting to mammography. These challenges are most evident in the current environment of heightened expectations for improved quality, timeliness, and communication, along with increasing stress, fatigue, and malpractice concerns. In conclusion, the authors present an alternative to traditional reporting that attempts to address some of these diverse challenges while incorporating the aforementioned initiatives and technologic developments. This approach uses a graphical symbol language that is directly mapped to a standardized lexicon (RadLex) and is automatically converted into a structured hierarchical text report, which can then be much more easily searched and analyzed. [ABSTRACT FROM AUTHOR]

Although imaging technologies have undergone dramatic evolution over the past century, radiology reporting has remained largely static, in both content and structure. Existing free-text (prose) reports have been criticized for a number of inherent deficiencies, including inconsistencies in content, structure, organization, and nomenclature. A number of new initiatives and technologies now present the radiology community with the unique opportunity to fundamentally change the radiology report from free to structured text. These new developments include a standardized nomenclature (RadLex), automated information technologies (picture archiving and communications systems and electronic medical records), and automated data tracking and analysis software (natural-language processing). Despite the increasing availability of these tools and technologies for revolutionizing reporting, clinical, psychologic, legal, and economic challenges have collectively limited structured reporting to mammography. These challenges are most evident in the current environment of heightened expectations for improved quality, timeliness, and communication, along with increasing stress, fatigue, and malpractice concerns. In conclusion, the authors present an alternative to traditional reporting that attempts to address some of these diverse challenges while incorporating the aforementioned initiatives and technologic developments. This approach uses a graphical symbol language that is directly mapped to a standardized lexicon (RadLex) and is automatically converted into a structured hierarchical text report, which can then be much more easily searched and analyzed. [Copyright &y& Elsevier]

The authors review a decade’s experience in the nation’s first filmless radiology department and outline the challenges and rewards of the transition. They summarize their experience with 10 cautionary and informative lessons on making the process more successful, more efficient, and less stressful. A number of possible avenues of new research and assessment on the effects of filmless operation on radiologists, imaging staff, referring clinicians, and patients are highlighted. [Copyright &y& Elsevier]