Viz.ai, the leader in AI-powered disease detection and intelligent care coordination, today announced clinical data validating the impact of Viz LVO in the management and outcomes of patients with large vessel occlusions (LVO), a type of ischemic stroke that occurs when a major artery in the brain is blocked. Viz LVO, part of the Viz Neuro suite of artificial intelligence (AI)-powered solutions, automatically detects and triages suspected LVO patients and has been shown to reduce delays in acute stroke treatment.
The real-world study, “Should they stay or should they go? Stroke transfers across a hospital network pre- and post-implementation of an automated image interpretation and communication platform,” evaluated the clinical impact of Viz LVO on the rate of transfers resulting in endovascular thrombectomy (EVT) and associated costs before and after implementation of an AI-based software. The study found that implementation of the Viz LVO software significantly increased computed tomography angiography (CTA) use and transfers treated with EVT with an associated increase in spoke revenue and potential lower payor costs.
“Our findings highlight the efficacy and practical application of AI in a clinical setting,” said James M. Bonner, DO, FACOEP, FACEP, Chairman of Emergency Medicine at Inspira Medical Center Mullica Hill. “We are proud to partner with Viz.ai and utilize their innovative solutions to continue advancing the management of patients with large vessel occlusions where every minute counts. The care that the spoke hospitals can deliver has been significantly enhanced by real time actionable data that Viz.ai has delivered for us.”
The transfer of an ischemic stroke patient with suspected LVO who does not undergo EVT at the comprehensive stroke center (CSC), sometimes referred to as a futile transfer,1,2 is taxing on providers, costly to healthcare systems, and displaces patients from their families. This study demonstrated the impact of implementing the AI-based system, which allowed the care team at the hub and spokes to quickly and reliably access, review, and comment on both non-contrast and contrast CT scans with automated alerts for suspected LVO.
“The findings from this study represent a crucial advancement in our continuous effort to enhance patient outcomes and reduce healthcare costs through AI,” said Prem Batchu-Green, Vice President of Clinical at Viz.ai. “By demonstrating the real-world benefits of Viz LVO on essential metrics like transfers, we are not only confirming the efficacy of our technology but also reinforcing our dedication to making a significant impact in healthcare for the betterment of patients, their caregivers, and healthcare teams.”
