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.

Validation and testing of all artificial intelligence (AI) algorithms is needed to eliminate any biases in the data used to train the AI, according to HIMSS.

VIDEO: Understanding biases in healthcare AI

Validation and testing of all algorithms is needed to eliminate any biases in the data used to train the AI, according to Julius Bogdan, vice president and general manager of the HIMSS Digital Health Advisory Team for North America.

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VIDEO: AI can help prevent clinician burnout

Julius Bogdan, vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America, discusses how artificial intelligence (AI) can help combat clinician burnout.

Julius Bogdan, vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America, explains several key artificial intelligence (AI) trends he sees across healthcare.

VIDEO: 9 key areas where AI is being implemented in healthcare

Julius Bogdan, vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America, explains several key artificial intelligence (AI) trends he sees across healthcare.

Julius Bogdan, vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America, explains considerations for healthcare system information technology (IT) management teams on the implementation of artificial intelligence (AI). He also discusses ideally how AI should be integrated into medical IT systems, and some of the issues AI presents in the complex environment of real-world patient care." #AI #HIMSS

VIDEO: How hospital IT teams should manage implementation of AI algorithms

Julius Bogdan, vice president and general manager of the HIMSS Digital Health Advisory Team for North America, explains considerations for healthcare IT teams on the implementation of artificial intelligence (AI).

Examples of new plaque reporting in the CAD-RADS 2.0 document. Left, an example from CAD-RADS 2 / P2 plaque burden with mild coronary stenosis (25-49%). Right, example of a CAD-RADS 5/ P3, with a focal, non-calcified occlusion of the proximal RCA (arrow) and severe amount of plaque (P3). #CADRADS #YesCCT #CTA #CCTA

New CAD-RADS 2.0 reporting for coronary CTA offers patient management recommendations

The document includes updated classification to established a framework for stenosis, plaque burden and plaque modifiers, including assessment of CT-FFR or myocardial CT perfusion.

The ASNC is one of several medical imaging societies asking Congress to repeal the appropriate use criteria (AUC) criteria mandate. They say it poses issues for clinicians and is becoming outdated by changes in CMS payment systems. The AUC requirements call for documentation using CVMS authorized software in order to show advanced imaging such as nuclear and CT is justified, or else Medicare payments might be withheld.

VIDEO: AMA will ask Congress to revise clinical decision support mandate for cardiac imaging

American Society of Nuclear Cardiology (ASNC) delegates to the American Medical Association (AMA) House of Delegates 2022 meeting Stephen Bloom, MD, and Nishant Shah, MD, explain a new AMA policy asking Congress to revise its clinician decision support mandate. 

DiA Imaging Analysis, which specialized in developing the AI-based automated cardiac ultrasound solution LVivo Seamless. The technology is now integrated through partnerships with dozens of healthcare vendors, including ScImage, GE Healthcare, Philips Healthcare Konica Minolta and IBM Watson.

ScImage latest vendor to adopt DiA Imaging Analysis AI for echocardiography

Artificial intelligence vendor DiA has emerged as a key third-party provider of AI to larger imaging vendors.

Imaging shows COVID vaccines effective at warding off pulmonary embolism

Researchers have found the condition significantly less among patients who received at least two doses of a COVID vaccine.

Around the web

Ron Blankstein, MD, professor of radiology, Harvard Medical School, explains the use of artificial intelligence to detect heart disease in non-cardiac CT exams.

Eleven medical societies have signed on to a consensus statement aimed at standardizing imaging for suspected cardiovascular infections.