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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The new ‘normal’: Quality initiative brings clarity to radiology reporting

Making these resources more accessible to patients and referring providers will be crucial in the coming era of consumer-focused care, researchers argued in a new study.

February 7, 2020

How one institution is using PACS-based movies, GIFs to advance radiology education

Cinebot allows users to convert multi-frame images into sharable video resources with one-click, and it has been a hit so far, researchers wrote in the Journal of Digital Imaging.

February 6, 2020

Radiologists don't trust outside imaging exams, even with easier access

A new survey found many physicians were not confident in the quality of interpretations performed outside of their own institution, signaling even seamless access to secondary resources may not reduce double-imaging.

February 5, 2020
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New research validates O-RADS for reporting ovarian, uterine masses

The Ovarian-Adnexal Reporting Data System Magnetic Resonance Imaging score can help physicians create a patient-centered approach and potentially prevent unnecessary surgeries. 

January 27, 2020
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New framework pushes radiology toward fully automated triage system for thyroid cancer

Stanford University researchers found their method diagnosed nodules as accurately as expert classifiers and would have avoided a number of unnecessary biopsies in the process.

January 22, 2020

Man vs. machine: Human CDS reduces inappropriate imaging, cuts costs

As healthcare continues its hunt to reduce excessive imaging, Yale New Haven Hospital has found its clinical decision support intervention to be remarkably effective.

January 21, 2020

How one institution successfully introduced BT-RADS to radiologists

Emory University researchers found their website helped imaging experts understand and implement the brain tumor reporting and data system.

January 20, 2020
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21st century PACS: 4 ways blockchain could change the radiology landscape

Two imaging experts believe the ledger technology holds some of the same potential to change the field as picture archiving and communication systems did decades ago.

January 16, 2020

Around the web

Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.

Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans. 

"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday. 

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