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.

Radiomics-based tool predicts fracture risk in COPD patients
Such technology can be leveraged to improve risk assessments without accruing additional expenses for patients or clinicians, potentially filling in gaps where DXA exams fall short.
Many radiology PowerPoints inadvertently put private health information at risk
Many of these files are still readily available online, and numerous contain PHI that is “easily accessible,” a new analysis reveals.
Incidental finding characteristics that warrant communication
Three factors are associated with true high-risk findings—imaging protocols for aortic valve implantation planning, imaging area, and cardiology department orders.
GPT-4 as accurate as neurologists in predicting final diagnosis based on MRI reports
The large language model can also outperform other human providers, radiologists included, new study shows.
Providing chatbots with guideline context significantly improves their imaging recs
With proper prompts and appropriate context, chatbots can play a valuable role in imaging referrals.

CVIS: Improving Departments from Within

In the current era of healthcare reform, spawned by the funding made available in the HITECH Act of February's stimulus package, there has been much discussion about producing transparent and quantifiable data on the performance of various departments.

October 9, 2009

CVIS, Cardiology PACS Widening Image Access

For cardiology PACS, the explosion of cardiac-related advances across imaging modalities has created demand for expanded capabilities beyond simple image storage and distribution, providing physicians with access to patient-specific information related to images and reports within the facility or externally. Meanwhile, with this increased volume of image data, cardiologists also need to have access to more extensive patient data, such as hemodynamic monitoring, EKG and electronic medical record (EMR) information to create structured reports.

March 11, 2009

Around the web

Cardiovascular Business

FDA approves AI startup’s new software for echo assessments

iCardio.ai, co-founded by a cardiologist, is part of the Cedars-Sinai Accelerator program. The startup has already announced new partnerships with Viz.ai, Abbott and others in the cardiac health space.

Cardiovascular Business

Medicare administrative contractors approve coverage of AI-enabled quantitative CT

Four of the seven Medicare Administrative Contractors (MACs) announced they will now cover artificial intelligence-enabled quantitative coronary tomography (AI-QCT) and coronary plaque analysis (AI-CPA).

Radiology Business

ACR shares guidance for radiology providers facing IV supply shortages after hurricane

Baxter’s North Cove manufacturing site was significantly impacted by unprecedented rain and storm surge from Hurricane Helene hitting western North Carolina.

Enterprise Imaging

Radiomics-based tool predicts fracture risk in COPD patients

Many radiology PowerPoints inadvertently put private health information at risk

Incidental finding characteristics that warrant communication

GPT-4 as accurate as neurologists in predicting final diagnosis based on MRI reports

Providing chatbots with guideline context significantly improves their imaging recs

Around the web