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

“Large academic institution cuts incidental pulmonary embolism radiologist wait time by 78% with Aidoc AI triage” documents a Medical Imaging & Radiology deployment in Hospital & Health System at Large Academic Institution (unnamed). www.aidoc.com reports wait time reduction: 78%; 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.

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

The Challenge

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.

The Solution

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.

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Vendor

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Details

Company Size
Enterprise
Company
Large Academic Institution (unnamed)
Evidence status
Automated evidence gate passed
Deployment timeframe
Not reported by source
Directory entry published
Source link checked

Cited source

www.aidoc.com

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