Adventist Health Rideout

As a regional primary stroke center within a hub-and-spoke network, Adventist Health + Rideout faced manual bottlenecks that caused significant delays in transferring large vessel occlusion (LVO) stroke patients to comprehensive stroke centers. Average door-in-door-out (DIDO) times were 202 minutes, well above the Joint Commission's 120-minute benchmark. Delays in LVO identification and care-team notification were the primary drivers of poor outcomes.

The hospital deployed the Viz.ai platform as part of a comprehensive quality improvement initiative, combining real-time imaging analysis and automated care coordination with standardized transfer protocols and partnership with a comprehensive stroke center. Viz.ai enabled automated LVO detection from CTA imaging and immediate care-team notification, replacing a manual, multi-step transfer process with a real-time automated workflow.

Average DIDO times dropped from 202 minutes to 113 minutes — a 44% reduction that exceeded the Joint Commission's 120-minute benchmark by nearly 6%. Time from CTA completion to LVO detection fell by 84%, and care-team notification time was reduced from 45 minutes to just 7 minutes, accelerating access to endovascular reperfusion therapy.

• AI-driven imaging analysis can dramatically compress the critical window between stroke detection and transfer decision, directly impacting neurological outcomes.
• Combining technology deployment with standardized protocols and inter-hospital partnerships amplifies the impact beyond what either intervention achieves alone.
• Regional and community hospitals can meet or exceed national benchmarks for stroke care with the right AI-powered coordination tools.