Dear Healthcare Informatics Insider,
Healthcare IT has such a huge potential to revolutionize healthcare, both for caregivers and patients alike. But once it starts to work in an organization, people tend to take it for granted.
For organizations working to cost-justify their healthcare IT investments, the fact that this technology becomes rather transparent when successful is a pity. It helps for others to have tangible motivation. For this reason, the profile of University Medical Center Eppendorf (UKE) in Hamburg, by contributing writer Finn Snyder, describing how hospital-wide IT adoption has reduced costs and improved quality of care is impressive. Click here for the article.
Does your hospital or radiology department have a healthcare IT success story to share with other readers of the Healthcare Informatics Digital Community? If so, AuntMinnieEurope.com's editors would like to learn more.
The ability to mine all types of data for quantitative analysis is being made feasible, practical, and more affordable thanks to healthcare IT software. A session yesterday in Vienna at the European Congress of Radiology provided a glimpse into how powerful image analysis tools can be used for diagnostic analyses. Finn Snyder also covered this event, which you can read about here.
The importance of healthcare IT was not lost on a record crowd of more than 37,000 attendees at the Healthcare Information and Management Systems Society (HIMSS) annual meeting, which just concluded a week ago in Las Vegas.
Watch for a forthcoming in-depth interview by AuntMinnieEurope.com with HIMSS Executive Vice President of Global Services Jeremy Bonfini, who attended the event, to learn his perspective of the differences between Europe's needs and those of the U.S. and Canada.
![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&dpr=2&fit=crop&h=167&q=70&w=250)
