Large academic institution cuts incidental pulmonary embolism radiologist wait time by 78% with Aidoc AI triage

A large academic institution deployed Computer Vision & Medical Imaging for Medical Imaging & Radiology in Hospital & Health System. As reported by www.aidoc.com: 78% wait time reduction.

Maintained by Peter Korpak, Lead EditorHow evidence is checked
78%Wait Time Reduction
37.7 minutesAI-Flagged Median Wait Time
168.5 minutesStandard (Non-Flagged) Median Wait Time

Source-reported figures (cited source: www.aidoc.com)

What the large academic institution was trying to fix

Incidental pulmonary embolisms (iPE) detected on routine outpatient abdominal CT scans — which do not include dedicated chest imaging — faced prolonged wait times before radiologist review. Delayed identification of these potentially life-threatening findings risked delayed intervention for patients.

What the large academic institution deployed

Aidoc's AI-driven system was deployed to analyze 4,447 contrast-enhanced abdominal CT scans performed between January and July 2023. The system automatically flagged suspected iPE cases (3.2% of scans) and triggered priority notifications to radiologists, enabling faster triage without requiring dedicated chest CT protocols.

Results

AI-flagged cases achieved a median radiologist review wait time of 37.7 minutes, compared to 168.5 minutes for non-flagged cases — a 78% reduction. The study concluded that AI-triggered notifications significantly enhance workflow efficiency and expedite reporting of incidental PE, potentially enabling more timely clinical interventions.

Key Takeaways

  • AI prioritization can dramatically reduce time-to-review for incidental, life-threatening findings identified outside their primary imaging protocol.
  • Deploying AI on routine abdominal CT scans extends vascular detection coverage beyond dedicated PE imaging workflows.
  • A 3.2% flag rate suggests the system targets a clinically meaningful subset without overwhelming radiologist queues with false positives.

Evidence for the large academic institution's Medical Imaging & Radiology deployment

Reported outcome metrics
3 cited below
Cited source
www.aidoc.com
Last updated
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Limitation: The cited source does not identify the company.

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Large Academic Institution

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