Informatics

The goal of health informatics systems is to enable smooth transfer of data and cybersecurity across the healthcare enterprise. This includes patient information, images, subspecialty reporting systems, lab results, scheduling, revenue management, hospital inventory, and many other health IT systems. These systems include the electronic medical record (EMR) admission discharge and transfer (ADT) system, hospital information system (HIS), radiology picture archiving and communication systems (PACS), cardiovascular information systems (CVIS), archive solutions including cloud storage and vendor neutral archives (VNA), and other medical informatics systems.

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Cardiology group faces class-action lawsuit after cyberattack exposed patients’ personal data

Patients learned that their names, social security numbers, banking numbers and credit card information were all potentially exposed as a result of the attack.

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Cardiology group hit by cyberattack, exposing data of nearly 182,000 patients

Patient names, addresses, social security numbers and even medical histories were exposed as a result of the attack, which went unnoticed for more than two months. 

PHOTO GALLERY: Cardiac technologies on display at HIMSS 2023

Click through a series of photos of cardiology-related technologies from the world's largest health IT conference.

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.

An example of artificial intelligence (AI) automated detection of a intracranial hemorrhage (ICH) in. a CT scan used to send alerts to the stroke acute care team before a radiologist even sees the exam. Example shown by TeraRecon at RSNA 2022.

FDA has now cleared more than 500 healthcare AI algorithms

More than 500 clinical AI algorithms have now been cleared by the FDA, with the majority just in the past couple years.

An example of an FDA cleared radiology AI algorithm to automatically take a cardiac CT scan and identify, contour and quantify soft plaque in the coronary arteries. The Cleerly software then generates an automated report with images, measurements and a risk assessment for the patient. This type of quantification is too time consuming and complex for human readers to bother with, but AI assisted reports like this may become a new normal over the next decade. Example from Cleerly Imaging at SCCT 2022.

Legal considerations for artificial intelligence in radiology and cardiology

There are now more than 520 FDA-cleared AI algorithms and the majority are for radiology and cardiology, raising the question of who is liable if the AI gets something wrong.

Example of a cardiovascular information system (CVIS) cath lab reporting module with a coronary tree model that will auto complete sections of the report based on how the cardiologist modifies the model. Image from the ScImage booth at ACC 2022. Photo by Dave Fornell

VIDEO: 4 key trends in cardiovascular information systems, according to Signify Reseach

Signify Research shares the latest big trends in cardiovascular IT systems, including the role of EMR cardiology modules vs. third-party CVIS, structured reporting, integration into enterprise imaging and inclusion of ambulatory surgical centers. 

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