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Adventist Health and Rideout cuts stroke transfer times 44% with Viz.ai AI-powered care coordination

“Adventist Health and Rideout cuts stroke transfer times 44% with Viz.ai AI-powered care coordination” documents a Patient Flow & Hospital Operations deployment in Hospital & Health System at Adventist Health and Rideout. neuronewsinternational.com reports dido time reduction: 44% (202 min → 113 min); this directory has not independently verified that result.

Maintained by Peter Korpak, Founder & Chief AnalystHow evidence is checked

Evidence at a glance

Evidence status:
Automated evidence gate passed
Deployment timeframe:
Not reported by source
Reported outcome metrics:
3 cited below
Directory entry published:
Source link checked:

The source-link check confirms reachability, not independent re-verification of every claim.

44% (202 min → 113 min)DIDO Time Reduction
84%CTA-to-Detection Time Reduction
45 min → 7 minCare-Team Notification Time

Source-reported figures — cited source: neuronewsinternational.com

Adventist Health and Rideout
Metric Before After Impact
DIDO Time 202 min 113 min 44% reduction
CTA-to-Detection Time 84% reduction
Care-Team Notification Time 45 min 7 min 84% reduction

The Challenge

Adventist Health and Rideout, a regional primary stroke centre, faced manual bottlenecks that delayed stroke care in regional settings. The complex transfer process for large vessel occlusion (LVO) stroke patients to a comprehensive stroke centre (CSC) resulted in average door-in-door-out (DIDO) times of 202 minutes, well above the US Joint Commission's 120-minute benchmark.

The Solution

The facility implemented a comprehensive quality improvement initiative combining the Viz.ai platform, a formal CSC partnership, and standardised transfer protocols. Viz.ai provided real-time imaging analysis and automated care coordination, replacing manual workflows with automated LVO identification, team activation, and interhospital communication.

Results

Average DIDO times fell from 202 minutes to 113 minutes — a 44% reduction that beat the 120-minute national benchmark by nearly 6%. Time from CTA completion to LVO detection dropped by 84%, and care-team notification times fell from 45 minutes to just 7 minutes.

Key Takeaways

  • Automating LVO detection and care-team notification can eliminate the largest manual delays in regional stroke transfer workflows.
  • Combining AI tooling with standardised protocols and CSC partnerships produces compounding time savings beyond what technology alone achieves.
  • Regional hospitals can meet or exceed national stroke benchmarks (AHA-GWTG, Joint Commission) through AI-assisted workflow redesign without requiring a major facility upgrade.

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Vendor

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Details

Company Size
MidMarket
Evidence status
Automated evidence gate passed
Deployment timeframe
Not reported by source
Directory entry published
Source link checked

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