Michael Barbella, Managing Editor01.12.23
Viz.ai has released to market a full cardiology suite to speed and improve patient access to cardiovascular treatments.
The Viz Cardio Suite leverages artificial intelligence-powered disease detection, workflow optimization, and care team coordination to provide efficiencies in cardiovascular care delivery.
“Viz.ai is becoming adopted across U.S. health systems as the system of action. The Viz Cardio Suite brings these capabilities to cardiovascular disease, where optimal patient outcomes often depend on the patient reaching the right therapy fast,” Viz.ai CEO Chris Mansi said. “Not only does the Viz Cardio Suite leverage AI to detect more disease in more patients, but it also accelerates the care pathway. This can improve quality of care for patients and working practices for cardiologists, while at the same time increasing hospital revenue and reducing overall healthcare costs.”
Despite ongoing advances in diagnostics and therapeutics, heart disease remains the leading cause of death worldwide, largely due to delayed diagnosis or inefficient care pathways. With its Cardio Suite, Viz.ai is streamlining care pathways by improving patient identification, developing disease-specific workflows and connecting patients to the right provider in their medical journey.
The Viz Cardio Suite includes:
Viz.ai develops AI algorithms and machine learning to increase the speed of diagnosis and care, covering more than 200 million lives across 1,200-plus hospitals and health systems in the United States and Europe. The AI-powered Viz Platform is an intelligent care coordination solution that identifies more patients with a particular disease, informs critical decisions at the point of care, and optimizes care pathways and helps improve outcomes.
Reference
1 Overall time may vary based on the interpreting physician and imaging source.
The Viz Cardio Suite leverages artificial intelligence-powered disease detection, workflow optimization, and care team coordination to provide efficiencies in cardiovascular care delivery.
“Viz.ai is becoming adopted across U.S. health systems as the system of action. The Viz Cardio Suite brings these capabilities to cardiovascular disease, where optimal patient outcomes often depend on the patient reaching the right therapy fast,” Viz.ai CEO Chris Mansi said. “Not only does the Viz Cardio Suite leverage AI to detect more disease in more patients, but it also accelerates the care pathway. This can improve quality of care for patients and working practices for cardiologists, while at the same time increasing hospital revenue and reducing overall healthcare costs.”
Despite ongoing advances in diagnostics and therapeutics, heart disease remains the leading cause of death worldwide, largely due to delayed diagnosis or inefficient care pathways. With its Cardio Suite, Viz.ai is streamlining care pathways by improving patient identification, developing disease-specific workflows and connecting patients to the right provider in their medical journey.
The Viz Cardio Suite includes:
- Mobile ECG Viewer, which allows care teams to quickly and easily access and view all 12-lead ECGs flowing through the health system; compare ECGs to previous ones; and share high-quality ECGs via HIPAA-compliant app
- A Mobile and Web Cardiac Imaging Viewer, which allows care teams to save time and access images on the go
- A Pre-PACS Chest CT Viewer
- In-application cardiology consultation
- Patient data acquisition through CVIS and EHR integration
- Complete AI-structured echo reports in less than two minutes,1 in partnership with Us2.ai
Viz.ai develops AI algorithms and machine learning to increase the speed of diagnosis and care, covering more than 200 million lives across 1,200-plus hospitals and health systems in the United States and Europe. The AI-powered Viz Platform is an intelligent care coordination solution that identifies more patients with a particular disease, informs critical decisions at the point of care, and optimizes care pathways and helps improve outcomes.
Reference
1 Overall time may vary based on the interpreting physician and imaging source.
