CareSelect

Eliminate Waste and Control Costs

Amena Hassan, American College of Radiology

ACR Case Study: Engaging the Physician

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Sometimes the best patient care involves no imaging at all. So when the radiologists at Baylor College of Medicine noticed that some referring physicians were ordering more MRIs for low back pain than seemed appropriate, they took the lead to study the situation and deploy a solution for improved patient care.

In doing so, the radiologists turned to the ACR’s Radiology Support, Communication, and Alignment Network (R-SCAN™), an innovative quality improvement initiative that brings radiologists and referring clinicians together to enhance image ordering and reduce unnecessary imaging.

ESR announces new ESR iGuide portal to support its quality and safety mission

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Monday, December 11, 2017 (ESR, Vienna) – The European Society of Radiology (ESR) announces the launch of a new ESR iGuide web portal to widen access to the ESR imaging referral guidelines. To be launched by the European Congress of Radiology 2018 (February 28–March 4), the stand-alone version of the ESR iGuide clinical decision support system is designed to help ESR members, referring physicians, healthcare organisations and EU and IAEA member states comply with European and international radiation protection standards. By making this announcement during the IAEA International Conference on Radiation Protection in Medicine, where the ESR is a cooperating organisation, the ESR hopes to raise awareness in Europe and beyond of the importance of the appropriate use of medical imaging.

RSNA 2017: The Year of Image Augmentation

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Last week was the conclusion of the annual Radiological Society of North America (RSNA) in Chicago.  The RSNA has always been an imaging-heavy affair, but this year it seems to have been afflicted with a dose of augmentation.  While imaging is still the primary focus, it seems that radiology has awoken to the age of population health management and value-based care, and vendors are beginning to place greater emphasis on how imaging diagnostics can be augmented by artificial intelligence and machine learning.