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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MRI radiomics could change the future of breast cancer treatment

Radiomics methodologies could change how care plans are managed for patients with breast cancer by identifying those most likely to benefit from specific treatments.

University of Rochester Medical Center in the US selects Sectra Enterprise Imaging in the cloud

Linköping, Sweden and Shelton, CT – October 17, 2022– International medical imaging IT and cybersecurity company Sectra (STO: SECT B) will provide enterprise imaging as a cloud subscription service (Sectra One Cloud), throughout the University of Rochester Medical Center (URMC). This will allow the US health system scalability as enterprise imaging volumes grow, in a secure and fully managed cloud environment.

An example of commercially available artificial intelligence (AI) automated grading of breast density on mammograms from the vendor Densitas..

VIDEO: Role of AI in breast imaging with radiomics, detection of breast density and lesions

Connie Lehman, MD, chief of breast imaging, co-director of the Avon Comprehensive Breast Evaluation Center at Massachusetts General Hospital, discusses how artificial intelligence (AI) is being implemented in breast imaging.

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What is the radiologist's role in variations of prostate cancer detection?

Prior studies have focused on radiologist performance rather than patient outcomes, leaving the topic of variable diagnoses and what factors impact them—race, ethnicity, age, biopsy type, etc.—open for debate. 

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VIDEO: KLAS shares trends in enterprise imaging and AI

Monique Rasband, vice president of imaging, cardiology and oncology, KLAS Research, explains some of technology trends KLAS researchers have found in enterprise imaging system and radiology artificial intelligence (AI).

Charles E. Kahn, Jr., MD, MS, Editor of the the journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine. He has been heavily involved in radiology informatics and has seen up close the evolution of radiology toward deeper integration with AI. #RSNA

VIDEO: Use cases and implementation strategies for radiology artificial intelligence

Charles Kahn, Jr., MD, editor of the the journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine, explains the work involved integrating AI in radiology systems and the role of AI in augmenting patient care.
 

Charles E. Kahn, Jr., MD, MS, editor of the the RSNA journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine. He discusses the need to validate artificial intelligence (AI) algorithms with your own patient population to determine if it is accurate for a specific institutions patients. He also explains how bias can be inadvertently added into a algorithm, and how the AI may take learning shortcuts. #AI

VIDEO: Assessing radiology AI and understanding programatic bias 

Charles E. Kahn, Jr., MD, MS, editor of the the RSNA  journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine, discusses the need to validate AI algorithms with your own patient population data.  

Specialty-specific workflow training could increase radiologist satisfaction with EHRs

Clinicians who receive specialty-specific workflow training are 24 times more likely to agree that the EHR meets their functionality needs, according to a new KLAS report.

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Around the web

Radiology Business
Tariffs threaten imaging access for patients, RBMA warns

Radiology practices are already operating on razor thin margins, with price increases prompting calls for congressional action to prevent further damage. 

Radiology Business
Chinese radiology vendors dodge high tariffs with US-based factories

United Imaging and other manufacturers that have established American factories may remain insulated from the trade war.

Radiology Business
Radiology groups face hardships under the Medicare MIPS program

Erik Rockswold, director research and quality, Rayus Radiology, explains the administrative burdens radiology groups experience for little return from the Merit-Based Incentive Payment System.