New Data Demonstrate Benefits of Viz.ai’s Stroke Treatment Tech

Viz.ai is sharing clinical data validating the impact of Viz LVO in the management and outcomes in patients with large vessel occlusions (LVO), a type of ischemic stroke.

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. LVOs occur when a major brain artery is blocked.
 
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 Viz LVO’s clinical impact on transfer rates resulting in endovascular thrombectomy (EVT) and associated costs before and after implementing artificial intelligence (AI)-based software. The study found that implementing 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., chairman of Emergency Medicine at Inspira Medical Center Mullica Hill. “We are proud to partner with Viz.ai and utilize their 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,” Viz.ai Vice President of Clinical Prem Batchu-Green stated. “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.”
 
Viz.ai uses AI algorithms and machine learning to increase the speed of diagnosis and care across more than 1,700 U.S. and European hospitals and health systems. The AI-powered Viz.ai One is an intelligent care coordination solution that identifies more patients with a suspected disease, informs critical decisions at the point of care, optimizes care pathways, and helps improve outcomes. 

References
¹ Fuentes B, De Leciñana M A, Ximénez-Carrillo A, et al. Futile interhospital transfer for endovascular treatment in acute ischemic stroke: the Madrid stroke network experience. Stroke 2015; 46: 2156–2161.
² Sablot D, Dumitrana A, Leibinger F, et al. Futile interhospital transfer for mechanical thrombectomy in a semirural context: analysis of a 6-year prospective registry. J NeuroIntervent Surg 2019; 11: 539–544.