Enterprise Imaging

Enterprise imaging brings together all imaging exams, patient data and reports from across a healthcare system into one location to aid efficiency and economy of scale for data storage. This enables immediate access to images and reports any clinical user of the electronic medical record (EMR) across a healthcare system, regardless of location. Enterprise imaging (EI) systems replace the former system of using a variety of disparate, siloed picture archiving and communication systems (PACS), radiology information systems (RIS), and a variety of separate, dedicated workstations and logins to view or post-process different imaging modalities. Often these siloed systems cannot interoperate and cannot easily be connected. Web-based EI systems are becoming the standard across most healthcare systems to incorporate not only radiology, but also cardiology (CVIS), pathology and dozens of other departments to centralize all patient data into one cloud-based data storage and data management system.

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Veteran researchers share the benefits, challenges of multicenter radiology research

Multicenter research studies, published collaborations between at least three medical centers, are becoming increasingly common in some healthcare specialties—but not radiology. A team of researchers explored this trend, surveying published academics about such studies, and published their findings in Academic Radiology.

Cincinnati Children’s Acquires Advanced CT Technology to Improve Pediatric Patient Care

Aquilion ONE / GENESIS Edition Delivers Fast, Safe Exams for Young Patients

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Northeast boasts most radiology residents, greatest job shortages

New research in the Journal of the American College of Radiology suggests the Northeastern United States has the highest per capita number of radiology residents, despite being the region most affected by job shortages.

ACR 2018 Call for Abstracts: Bring Focus to Radiology Research

Abstract Submission Opens for American College of Radiology Annual Meeting; Online Submission Closes Dec. 15

Radiology grapples with looming machine learning ‘threat’

Machine learning is quickly becoming a game changer within radiology.

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Progress through teamwork: 2 key collaborations between radiologists, scientists

Collaborating with various scientific disciplines has been essential for radiology’s growth over the years, according to a recent analysis published in Academic Radiology. Without the specialty reaching out and working with scientists in these other fields, it’s hard to imagine radiology as we know it today even existing.

Tennessee Hospital Installs Carestream’s Clinical Collaboration Platform to Expedite Enterprise Viewing, Diagnostic Reading

ROCHESTER, N.Y., Aug. 22 — Regional One Health (Memphis, Tenn.) has implemented Carestream Health’s Clinical Collaboration Platform (see video link) that includes enterprise imaging, vendor-neutral archiving and Vue Motion universal viewer.

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When this process was simplified, the entire department benefited

Making significant workflow changes at large academic medical centers can be quite difficult, but a team of researchers at the Vanderbilt University Medical Center (VUMC) in Nashville, Tennessee, were able to do just that. Lead author Richard G. Abramson, MD, and colleagues shared their success in the Journal of the American College of Radiology, providing an in-depth look at what they changed and the impact it had on the entire radiology department.

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Around the web

Health Imaging
MRI projectile incident likely to result in a 'seven-figure sum' repair bill for hospital

News of an incident is a stark reminder that healthcare workers and patients aren’t the only ones who need to be aware around MRI suites.

Health Imaging
American College of Radiology announces significant expansion of Lung Cancer Screening Registry

The ACR hopes these changes, including the addition of diagnostic performance feedback, will help reduce the number of patients with incidental nodules lost to follow-up each year.

Health Imaging
AI reduces CT lung cancer screening workload by nearly 80%

And it can do so with almost 100% accuracy as a first reader, according to a new large-scale analysis.