Amsterdam, the Netherlands and Chicago, Ill – At the 2018 Radiological Society of North America Annual Meeting (RSNA), Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, today announced that radiologists at the University of Utah Health are leveraging Philips Illumeo with adaptive intelligence to interact with imaging data to enhance physician expertise and efficiency. Initial results include productivity benefits in turnaround time, same day readings, and context driven tool selection.
Artificial intelligence (AI)-based solutions have the potential to increase the efficiency of care delivery and improve patient care. Through solutions that combine AI and other technologies with knowledge of the clinical and operational context in which they are used, Philips provides a people-centered approach called adaptive intelligence. This augments the capabilities of clinicians to seamlessly connect people, data and technology to empower radiologists.
University of Utah Health provides care for residents of Utah and five surrounding states, with a referral area that encompasses more than 10 percent of the continental U.S. Due to this large volume of coverage and an increase in imaging data, the radiology department faces increasing amounts of imaging studies and data that need to be processed – about five hundred thousand per year. The health system selected to implement Illumeo, an imaging and informatics technology with adaptive intelligence, to intelligently interact with imaging data. Illumeo combines contextual ques and Anatomy Awareness capabilities with advanced data and image processing to augment the radiologist’s routine activities. The technology supports interactions with imaging data comparisons and provides an integrated view of clinically relevant, case-related information from various sources, designed to optimize workflow and enhance care consistency.
“Illumeo leverages adaptive intelligence and analytics1 to anticipate what a radiologist needs to do next, allowing him/her to interact with imaging data in a much more intelligent way,” said Richard Wiggins, MD, Professor of Radiology and Imaging Sciences, University of Utah Health. “The solution moves beyond just hanging protocols, by providing a faster way for radiologists to find all similar series of studies and compare them side-by-side to see if lesions are getting larger over time. This new technology allows us to further improve time savings and efficiencies so we can provide the best care to our patients.”2
