Dear PACS Insider,
The RSNA's Image Share project isn't the only image sharing initiative to receive grant funding from the U.S. National Institutes of Health's National Institute of Biomedical Imaging and Bioengineering. The institute also provided funds for a six-hospital consortium in central Alabama to launch an Integrating the Healthcare Enterprise (IHE) Cross-Enterprise Document Sharing for Imaging (XDS)-based image exchange network.
The Central Alabama Health Image Exchange (CAHIE) is expected to launch shortly, and Dr. Barton Guthrie of the University of Alabama at Birmingham shared details of the project during a presentation at the recent Society for Imaging Informatics in Medicine (SIIM) annual meeting.
Our coverage of CAHIE is the subject of this month's PACS Insider Exclusive, which you can access before the rest of our AuntMinnie.com members by clicking here.
As mobile applications are changing the way medical images are viewed, institutions have a number of issues to address in order to successfully use tablet devices for this purpose, according to another SIIM presentation. Find out more here.
In other current coverage from SIIM, integrating digital photos within PACS may be able to help decrease patient identification errors. Also, radiology providers should not ignore social media.
Images from external institutions should not be stored permanently within an enterprise PACS archive, according to researchers from the University of Utah. Find out why by journeying here.
Also in your PACS Digital Community, find out what imaging informatics experts from the Millennial Generation think about the future of medical imaging by clicking here.
In other news, research firm KLAS is reporting that most healthcare providers in the U.S. are still in the early stages of forming an enterprise imaging strategy. You can also learn how MPEG-4 compression may be an option for sending large cross-sectional imaging studies over the low-bandwidth networks often found in remote areas by visiting here.
PACS-integrated lung CT computer-aided detection (CAD) technology was also recently shown to increase reader sensitivity for detecting lung nodules in thoracic CT exams.
Do you have a topic you'd like to see covered, or are you interested in submitting an article? Please feel free to drop me a line.
