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.

Video interview with ACR CEO Dana Smetherman, MD, who explains how the American College of Radiology can help radiology practices evaluate and vet AI.

ACR offers resources to achieve radiology AI best practices

Dana Smetherman, MD, CEO of the American College of Radiology, explains resources available through its Data Science Institute to evaluate and validate the quality of imaging algorithms.

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EHR intervention cuts unnecessary MRI orders by 35%

Many of these exams are ultimately deemed normal, and their results often do not affect how patients’ headaches are managed. 

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Why PACS should be part of undergrads' medical education

Many traditional radiology courses leave out hands-on opportunities for students—something that could greatly benefit their understanding of the specialty.

Example of AI automated detection and highlighting of critical lung findings on a chest X-ray for a possible lung cancer nodule and fibrosis. Example shown by AI vendor Lunit.

PHOTO GALLERY: Examples of FDA-cleared AI in radiology

This is a photo gallery of artificial intelligence products cleared for clinical use in medical imaging by the U.S. Food and Drug Administration. Radiology by far is the leader of all clinical AI FDA approvals.

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ChatGPT's medical writing is getting so good that it may soon fool AI detectors

The large language model’s medical manuscripts are becoming so well constructed that it can be difficult to distinguish them from those compiled by humans. 

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Providers' opinions on giving patients open access to their radiology reports are evolving

Online access to medical records has become standard practice, making sharing radiology reports and communicating findings much more streamlined.

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AI rules out abnormal findings on chest X-rays, significantly reducing workloads

The commercially available software can correctly exclude pathology on chest radiographs with accuracy rates similar to those of radiologists.

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How GPT-4 can improve radiology resident report feedback

With resources stretched thin at many facilities, this type of feedback can often be limited.

Around the web

CMS has more than doubled the CCTA payment rate from $175 to $357.13. The move, expected to have a significant impact on the utilization of cardiac CT, received immediate praise from imaging specialists.

The newly cleared offering, AutoChamber, was designed with opportunistic screening in mind. It can evaluate many different kinds of CT images, including those originally gathered to screen patients for lung cancer. 

AI-enabled coronary plaque assessments deliver significant value, according to late-breaking data presented at TCT. These AI platforms have gained considerable momentum in recent months, receiving expanded Medicare coverage in addition to a new Category I CPT code.

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