Dear Healthcare Informatics Insider,
PACS technology is continuously evolving in Europe. In spite of the impressive improvements made during the past two decades, integration issues are still of concern.
Guest columnist Dr. Neelam Dugar, who chairs the U.K. Royal College of Radiologists' Imaging Informatics Group, offers sage advice. She reiterates the importance of specifying Integrating the Healthcare Enterprise (IHE) profiles, and explains why they are so important. Click here to read why it's necessary to be proactive.
Case studies are also useful. We're featuring a two-part article on the evolution of a super-PACS in Israel. The Clalit health organization's radiology units all went digital in 2006, but fully integrating them required the newest technology. Click here and here to read Associate Editor Frances Ryland-Monk's insightful observations.
Imaging will play an important role as personalized medicine continues to evolve this decade. In late June, International Editor Eric Barnes attended the Computer Assisted Radiology and Surgery (CARS) annual meeting and reported on a session dedicated to this subject. Another controversial topic at CARS was using open-source software, which Eric reported in depth here.
AuntMinnieEurope.com has received numerous market reports and projections during recent weeks. One that particularly interested us was the prediction that computerized physician order entry (CPOE) systems would gain a foothold and evolve into an industry worth tens of millions of euros during the next five years in Europe.
We'd like to know if hospitals or members of the Healthcare Informatics Digital Community are using CPOEs. If so, how well are they working at ordering the most appropriate imaging examinations using evidenced-based guidelines? Please send us an email with your comments.
And if you have other comments or suggestions, we'd like to hear from you. Meanwhile, enjoy the rest of the summer!















![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)


