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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Emit Trivedi, Healthcare Information Management Systems Society (HIMSS) director of informatics and health IT standards, discussed these challenges of next-level interoperability with Health Exec at the HIMSS 2023 annual meeting. #HIMSS #HIMSS23 #HIMS2023 #interoperability

What missing pieces remain in health IT interoperability?

Amit Trivedi, HIMSS director of informatics and health IT standards, explains the remaining gaps in interoperability and how it remains a moving target.

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AI model identifies radiologist-recommended follow-up imaging in reports, has potential for widespread use

New data published in the American Journal of Roentgenology details the performance of a deep learning model known as BERT, short for Bidirectional Encoder Representations from Transformers.

Brain imaging artificial intelligence is a primary area of concentration for AI because oif the critical nature of fast detection and treatment for patients. This is an example of the AI applications displayed by third-party advanced visualization vendor TeraRecon at RSNA 2022.

What is the ROI on AI adoption in radiology?

Radiology makes up the vast majority of FDA-cleared AI algorithms, but with minimal or no reimbursement, hospital administrators may ask whether AI’s value justifies its expense.

pulmonary embolism on CT pulmonary angiography

AI work list prioritization tool significantly decreases PE turnaround times

The FDA-approved tool works by reprioritizing CTPA exams to the top of a radiologist’s work list when the scan is positive for PE.

Rankings of radiology IT solutions by end-users in the 2023 Best in KLAS program

End-users of various radiology IT systems offer their assessment of the software in the annual KLAS Research 2023 Best in KLAS report.

KLAS 2023 rankings for cardiovascular information systems and hemodynamic solutions

Hospital end-users ranked the CVIS and hemodynamic systems they are using and shed light on their working relationships with IT vendors. 

The integration of artificial intelligence (AI) into radiology PACS and enterprise imaging systems has become a big topic of discussion with IT vendors over the past couple years. This has become a bigger question from hospitals and radiology groups as there are now about 400 radiology related AI algorithms that have U.S. Food and Drug Administration (FDA) clearance. Amy Thompson, a senior analyst at Signify Research, is monitoring AI trends in radiology and discusses trends.

Trends in the adoption and integration of AI into radiology workflows

Amy Thompson, a senior analyst at Signify Research, explains why AI adoption has been slow in radiology, common barriers and trends in the market.

Amy Thompson, a senior analyst at Signify Research, explains what she is seeing in the market for radiology PACS. She said the biggest overall, strategic technology trends are wider adoption of enterprise imaging systems expanding beyond radiology to include other departments, migration to cloud data storage, and adoption of artificial intelligence. Components of these integrate into the 5 trends in radiology IT systems outlined below.

5 key trends in PACS and enterprise imaging from Signify Research

Signify Research explains several key trends in the evolution of radiology PACS and enterprise imaging systems, including adoption of artificial intelligence, streamlining workflow, implementing structured reporting and more.

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