Previous studies have demonstrated that imaging overuse is pervasive in the ED, with “defensive medicine” a common reason, experts wrote in JAMA Network Open.
Example of AI automated detection and highlighting of critical lung findings on a chest X-ray for a possible lung cancer nodule and fibrosis. Example shown by AI vendor Lunit.
This is a photo gallery of artificial intelligence products cleared for clinical use in medical imaging by the U.S. Food and Drug Administration. Radiology by far is the leader of all clinical AI FDA approvals.
A recent 2024 PocketHealth survey of 202 U.S. hospital and imaging center decision-makers highlights the significant challenges healthcare providers face with legacy image exchange systems. The survey and conversations with industry leaders reveal that these outdated solutions impact both operational efficiency and patient satisfaction, often resulting in additional workload and increased costs.
Commitment to work-life balance, physician autonomy, positive atmosphere and management that treats staff well were listed as key elements of a healthy workplace.
"This reduced talent pool, coupled with increasing demands in radiology, will negatively affect the quality and access to care for patients," experts wrote in JACR.
