Viz.ai Study Demonstrates Significant Reduction in Interfacility Stroke Transfer Times

New clinical data show a 44% reduction in door-in-door-out (DIDO) time—the amount of time required to evaluate, coordinate, and transfer a patient to a comprehensive stroke center—for patients with large vessel occlusion (LVO) stroke in regional care settings.

The study, “Bridging the Gap: Leveraging AI Technology & Partnerships to Meet DIDO Benchmarks for LVO Patients,” led by Caezar G. Jara at Adventist Health + Rideout, evaluated the impact of the Viz.ai platform on DIDO times at a regional primary stroke center within a hub-and-spoke network. For stroke patients in regional or community settings, DIDO time is a critical determinant of outcomes. Following the implementation of a comprehensive quality improvement initiative—including deployment of the Viz.ai platform, a partnership with a comprehensive stroke center, and standardized transfer protocols—average DIDO times decreased from 202 minutes to 113 minutes, exceeding the Joint Commission’s 120-minute national benchmark by nearly 6%.

Performance gains were driven by faster LVO identification and team activation, including an 84% reduction in time from CTA completion to detection and a reduction in care-team notification time from 45 minutes to seven minutes. These workflow changes occurred in the context of implementing Viz.ai’s real-time imaging analysis and automated care coordination capabilities as part of a broader quality improvement effort.

“Our initiative was driven by the need to eliminate manual bottlenecks that delay stroke care in regional settings,” said Jara, stroke program manager at Adventist Health + Rideout. “By integrating Viz.ai, we replaced a complex transfer process with an automated, real-time workflow, helping patients reach life-saving intervention sooner.”

In acute ischemic stroke, every minute of delay results in the loss of 1.9 million neurons.¹ By significantly reducing time to definitive care, the Viz.ai platform enables faster access to endovascular reperfusion therapy, which is associated with improved functional outcomes and reduced disability.

“The data underscore the power of AI-powered care coordination to expand equitable access to advanced stroke care across regional and community settings,” Viz.ai Associate Product Director Chelsea Summerour stated. “Achieving nearly a 90-minute reduction in DIDO time relative to historical performance and aligning with American Heart Association Get With The Guidelines (AHA–GWTG) transfer standards represents a measurable clinical and system-level advancement, accelerating access to endovascular therapy for patients who might otherwise face preventable delays.”

Designed to support regional and community hospitals, Viz Assist integrates real-time patient context, automates care-team activation, standardizes transfer workflows, and streamlines inter-hospital communication. By aligning imaging insights with operational coordination across hub-and-spoke networks, Viz Assist helps reduce variability in transfer decision-making and accelerates access to endovascular reperfusion therapy, according to the company.

Viz.ai builds and deploys artificial intelligence (AI)-powered Care Pathways and helps doctors with their work. The Viz Platform is deployed in 2,000 U.S. hospitals and trusted by many life sciences companies. The platform combines real-time, multimodal clinical data with deep clinician engagement to detect disease earlier, coordinate care teams, and help ensure patients receive the proper treatment faster. Viz.ai was the first company to be awarded CMS reimbursement for AI and is ranked the top Healthcare AI Platform by hospitals and health systems in the Black Book Research survey.

Reference
¹ Saver JL. Time is brain—quantified. Stroke. 2006;37(1):263-266. doi:10.1161/01.STR.0000196957.55928.ab