The rapid evolution of technology and healthcare expectations makes it both difficult and vital to adapt to the mercurial healthcare environment. The success of radiology is predicated on our ability to adopt new technologies and ideas. For the past several years, the Radiology Research Alliance (RRA) of the Association of University Radiologists has examined new trends in society and health care, evaluated how these new trends impact the practice of radiology, and summarized these findings in our task force articles. The RRA continues this endeavor and this year is publishing six articles that examine ways radiology and radiologists may stay at the forefront of healthcare innovation. We are thankful for the thoughtful input of the reviewers and editors of these papers, and for the opportunity to share this information with the radiology community.
Task Force Topics
Radiology education has long focused on an apprenticeship model where residents work on a near one-to-one basis with their faculty mentors. Although effective, this approach may not adequately address all trainees’ educational needs during their tenure as residents and fellows. In their task force white paper “Conventional medical education and the history of simulation in radiology” that appeared earlier in the October 2015 issue of Academic Radiology , Chetlen et al. examine ways in which simulation may be used to supplement current radiology educational tools. They suggest that such simulation-based training in medicine will become an important tool in the training of radiologists given the changes in technology, learning, regulations, and societal expectations. They provide a comprehensive discussion of simulation as a tool for learning both procedural and nonprocedural skills, and an organized review of the currently available simulation equipment and software.
Health care is becoming increasingly data driven, not just from the delivery standpoint, but also from that of reimbursement. To have services reimbursed, it is becoming more important to demonstrate whether a given medical test or intervention positively affects patient outcomes. Zygmont et al. , in their examination of “Opportunities for Patient-centered Outcomes in Radiology,” discuss ways radiology can benefit from new methods in outcomes research. In particular, they discuss the national agenda for patient-centered outcomes research, focusing on imaging, funding opportunities, and the opportunities for such research to involve medical imagers and radiologists. Zygmont et al.’s article may assist medical imaging researchers interested in obtaining funding from the Patient-Centered Outcomes Research Institute.
Both healthcare consumers and payers are increasingly expecting value to be demonstrated and taken into account when deciding on where to allocate their financial resources. In “The Value of Imaging—Parts I and II,” Duong et al. provide an overview of methods for defining value in radiology, and suggest ways radiologists may demonstrate and deliver services with better value. Part I focuses on the perspective for the academic radiologist, beginning with a definition of the value in health care and in radiology, which is different from the traditional definition from economics. This paper includes a discussion of value metrics and how comparative effectiveness research may serve as a benchmark for evaluation of diagnostic tests and treatment methods. Part II delves into value beyond volume and image interpretation by proposing areas where radiologists can add additional value including standardization, imaging appropriateness and decision support, patient-radiologist communication, and improved communication between referring physicians and radiologists.
The amount of data being acquired and stored digitally is large, both for our society as a whole and in medicine in particular. Kansagra et al. tackle “Big Data and the Future of Radiology Informatics” by exploring tools for addressing the ever-increasing volume of data and how this will affect the practice of radiology. Specifically, they consider four big questions for radiology by considering how big data can (1) enable personalized image interpretation, (2) facilitate discovery of new imaging markers, (3) quantify the value of radiology services to patient care, and (4) characterize and optimize radiology workflows.
The complexities of and expectations for radiology research are increasing. The historical model of a solitary scientist pondering the nature of the universe and arriving at a moment of clarity where great discoveries are made is becoming less feasible. Current medical research is becoming increasingly dependent on a team approach. Decker et al. , through their “Research Challenges and Opportunities for Clinically Oriented Academic Radiology Departments” task force’s whitepaper address ways in which smaller institutions with more limited resources may be able to pool resources to perform high-quality research. They begin with a consideration of the barriers to high-quality research encountered at smaller institutions, followed by a presentation of their Clinically Oriented Academic Radiology Department Research Initiative collaboration model. Finally, they review research areas that are appropriate for this Clinically Oriented Academic Radiology Department Research Initiative model, which include public policy, comparative effectiveness research, quality improvement, imaging utilization, and education.
Future Task Force Topics
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References
1. Chetlen A.L., Mendiratta-Lala M., Probyn L., et. al.: Conventional medical education and the history of simulation in radiology. Acad Radiol 2015; 22: pp. 1252-1267.
2. Zygmont M.E., Lam D.L., Nowitzki K.M., et. al.: Opportunities for patient-centered outcomes research in radiology. Acad Radiol 2015;
3. Duong P.A., Bresnahan B., Pastel D.A., et. al.: The value of imaging part I: perspectives for the academic radiologist. Acad Radiol 2015;
4. Duong P.A., Bresnahan B., Pastel D.A., et. al.: The value of imaging part II: value beyond image interpretation. Acad Radiol 2015;
5. Kansagra A.P., Yu J.-P.J., Chatterjee A.R., et. al.: Big data and the future of radiology informatics. Acad Radiol 2015;
6. Decker S.J., et. al.: Research challenges and opportunities for clinically oriented academic radiology departments. publication information pending2015.