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Incidental Abnormalities in Radiology
Have you noticed that incidental abnormalities seem to be on the rise? This is largely due to advancements in imaging technology and improved patient care—when you order cross-sectional imaging for one problem, you are more likely to discover abnormalities that are unrelated to the primary problem. In fact, they’re showing up in about one-third of CT scans today.
This is causing a significant shift in patient care. Before, the radiology community didn’t have a standardized approach on how to handle incidental findings, also called incidentalomas. The lack of direction and confidence about what to do would often compromise patient care. In some cases, radiologists may have not even reported incidental findings to patients or their providers. As technology has improved and incidental abnormalities are being discovered more often, the medical community has improved its approach.
Radiologists are answering the call
Radiologists—and providers in general—are focusing more on incidental abnormalities than ever before. Recently, institutions have published evidence-based recommendations for incidental findings in multiple disease states. Currently, these include The Fleischner Society guidelines for incidental pulmonary nodules, Lung Reporting & Data System, (Lung-RADS) for lung cancer, Thyroid Imaging Reporting & Data System, (TI-RADS) for thyroid nodules, and USPSTF Society For Vascular Surgery guidelines for abdominal aortic aneurysms. Radiologists who identify incidentalomas should follow these recommendations to recommend next steps for patient care pathways and follow-up. Adherence to these guidelines depends on radiologists, providers and facilities—and ultimately the patients themselves. Some patients may need more immediate action, while some only require serial surveillance. Regardless, all incidental abnormalities need to be properly evaluated, communicated and followed up on.
Even with accepted guidelines, there is vast room for improvement. For example, 95% of lung nodules are discovered incidentally, but less than 30% of those patients will receive follow-up care based on recommended guidelines. In the case of abdominal aortic aneurysms (AAA), 90% of incidental patients require only serial surveillance to watch for progression, but that follow-up can be life-saving—the annual survival rate for a ruptured AAA is only 20%. Because patient adherence needs to improve and the process can be time-consuming, healthtech companies are developing software to help facilities manage patients with incidental findings. Facilities need a comprehensive solution based on the recommended guidelines for specific disease states, which starts with artificial intelligence (AI) that interprets radiology reports and identifies incidental abnormalities.
Eon’s incidental findings solution
Eon offers just such a platform with Eon Patient Management (EPM) solutions for multiple disease states, including lung cancer screening, incidental pulmonary nodules, abdominal aortic aneurysms, thyroid, pancreas, adrenal, renal and liver. EPM utilizes proprietary Computational Linguistics (CL), a form of AI that understands text and linguistic structure to interpret imaging reports and identify incidentals at up to 98% accuracy. EPM also offers end-to-end patient management and longitudinal tracking, including automated communication and follow-up that saves FTE time. Radiologists and providers can have confidence in the longitudinal tracking of identified incidentaloma patients. Administrators can be satisfied in the ROI from increased patient adherence, optimized workflow and increased downstream revenue. A partner like Eon helps health care providers go all the way to give patients the best care possible, even through the unexpected.