Imaging AI in Practice: A Demonstration of Future Workflow Using Integration Standards.

Artificial intelligence (AI) tools are rapidly being developed for radiology and other clinical areas. These tools have the potential to dramatically change clinical practice; however, for these tools to be usable and function as intended, they must be integrated into existing radiology systems. In a collaborative effort between the Radiological Society of North America, radiologists, and imaging-focused vendors, the Imaging AI in Practice (IAIP) demonstrations were developed to show how AI tools can generate, consume, and present results throughout the radiology workflow in a simulated clinical environment. The IAIP demonstrations highlight the critical importance of semantic and interoperability standards, as well as orchestration profiles for successful clinical integration of radiology AI tools. Keywords: Computer Applications-General (Informatics), Technology Assessment © RSNA, 2021.

Enabling the Next-Generation Radiology Report: Description of Two New System Standards.

Currently, most radiology reports are highly variable and consist of unconstrained narrative text. This variability limits the ability to extract information from the report to guide clinical care, populate a data registry, or support quality improvement. This article introduces two newly available standards that pertain to radiology reports. Management of Radiology Reporting Templates (MRRT) is an integration profile that defines the format and exchange mechanisms for radiology report templates. Digital Imaging and Communications in Medicine Part 20 defines how reports built using MRRT-based templates can be transmitted into an electronic health record (EHR). Together, these two standards enable new ways to improve report consistency and completeness, ensure proper clinical action, and improve the quality of patient care. Commercial and open-source developers are beginning to incorporate these standards into clinical systems. The authors use an example of a patient with an incidentally detected lung nodule to illustrate how these standards improve the exchange of information. The clinical scenario follows the use of the appropriate template through the completion of the radiology report, with the incidental finding structured and coded to enable automated follow-up in the EHR. ©RSNA, 2017.

IHE: a model for driving adoption of standards.

The development of communication standards in healthcare is a major ongoing engineering effort. While there is little doubt that this effort has made possible significant advances in the performance of healthcare information and imaging systems, overall levels of systems interoperability have not improved as dramatically as one might reasonably expect and the cost of implementing effectively integrated systems remains high. The lag between the development of information standards and their implementation in real systems and institutions is a genuine problem in healthcare. This paper describes an ongoing initiative that attempts to bring together healthcare professionals and industry experts to coordinate the implementation of standards in ways that enhance operational efficiency and the quality of patient care.