Reduce time for stroke detection by 44%
Target Audience
Emergency department physicians, healthcare researchers, hospital network administrators
Challenge
Stroke treatment outcomes depend critically on rapid response. Delays in mechanical thrombectomy often stem from slow diagnosis and fragmented communications among care teams. Traditional workflows involve complex pathways and communication barriers that delay critical treatment.
Solution Approach
Viz.ai uses AI algorithms to automatically analyze CT angiogram scans and detect potential large vessel occlusions within minutes. When a suspected LVO is detected, the platform immediately alerts the entire on-call stroke care team via mobile notifications with HIPAA-compliant secure messaging and real-time image sharing.
Value Add
A systematic review of 12 studies involving 15,595 patients demonstrated significant reduction in CT-to-treatment time. The system reduced door-to-groin puncture time by 11 minutes, and achieved 44% reduction in time from arrival to diagnosis. Now deployed across 1,500+ hospitals covering 230+ million lives in the U.S.
References
Viz.ai, CHI Memorial Neuroscience Institute, UTHealth McGovern Medical School
Read more here: https://www.viz.ai/news/new-studies-demonstrate-impact-of-vizais-stroke-solution
Image credentials: camilo jimenez/ Unsplash
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