Seamless transmission of coronary computed tomography angiography images and machine learning data can aid a care provider’s ability to identify and treat heart disease earlier.
WHY IT MATTERS
By automating the upload of CCTA scans, or CT angiograms, from local systems to Cleerly’s cloud service, clinicians can enhance the speed and accuracy of identifying atherosclerosis, the leading cause of heart disease.
Cleerly’s diagnostics measure and tailor reports on plaque build-up in the heart’s arteries. The new software streamlines image transfers to make the whole process faster for providers and improve patient outcomes.
The company claims on its website that its results are proven, and that the Cleerly digital care pathway is simpler, faster and more accurate, leading to earlier diagnosis.
“Proxy is a turnkey solution that gives physicians and providers more time to focus directly on a patient’s heart care while we manage their workflows and provide IT and security comfort,” said Nick Nieslanik, CTO of Cleerly, in the announcement.
“By removing the need for multiple systems and workflows, heart disease detection becomes the priority and lets us drive the necessary reporting and analytics insights to the various stakeholders quickly, meeting them right where they need.”
Providers install an OVA file and the software can act as an end point for receiving CT angiograms from various picture archiving and communication systems (PACS), and from vendor-neutral archives, according to the company.
Once received, each scan can be uploaded to the Cleery cloud server and shared with other providers and patients.
THE LARGER TREND
In July, Cleerly received $192 million in financing to ramp up capabilities about one year after the company launched. Backers led by T. Rowe Price included Heartland Healthcare Capital funds, Novartis, LRVHealth, Cigna Ventures and others.
To improve cardiovascular care, many organizations are studying AI-guided heart disease detection.
Last year the Mayo Clinic announced the results of a trial using AI-enabled electrocardiograms to increase the diagnosis of low ejection fraction, a sign of heart failure, in Nature Medicine.
While echocardiograms can measure and detect low ejection fraction, EKGs are more readily available and cost-efficient. When detected, the electronic health record would alert the clinician to follow up with an echocardiogram.
“The AI-enabled EKG facilitated the diagnosis of patients with low ejection fraction in a real-world setting by identifying people who previously would have slipped through the cracks,” said Dr. Peter Noseworthy, the Mayo Clinic cardiac electrophysiologist who was the study’s senior author.
Also last year, Yale researchers applied machine learning using data from two large clinical trials to develop a decision-support tool called ASSIST that can help cardiologists decide which imaging to use in caring for patients with coronary artery disease.
ON THE RECORD
“With Proxy, our goal is to be completely seamless and allow providers to better treat their heart patients,” Dr. James Min, founder and CEO of Cleerly, said in the announcement.
“The addition of Proxy to our portfolio will decrease the time in which providers receive our AI-based quantifiable disease analysis with a tool that fits directly into their workflows. This virtual appliance is another way we are improving how heart disease is identified, prevented and treated.”
Andrea Fox is senior editor of Healthcare IT News.
Email: [email protected]
Healthcare IT News is a HIMSS publication.