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Everlight Radiology

Everlight Radiology flags 200 monthly incidental PE cases and cuts read times up to 12% with Aidoc AI for NHS Trusts

Curated & reviewed by Peter Korpak, Founder & Chief Analyst, 100SignalsHow we verify
200 cases/monthMonthly iPE Cases Flagged
~12%Read Time Reduction (Pulmonary Embolism)
~10%Read Time Reduction (Hemorrhagic Stroke)

Vendor-reported figures — source: www.aidoc.com

The Challenge

NHS A&E departments faced severe backlogs, with nearly 40% of patients waiting beyond the 4-hour target and a 29% radiologist shortfall projected to reach 40% within five years. Teleradiology providers like Everlight must handle surging imaging volumes while ensuring urgent and incidental findings — such as pulmonary emboli appearing on non-dedicated scans — are not missed in high-pressure reporting environments.

The Solution

Everlight deployed Aidoc AI in 2019 across its NHS Trust partnerships, integrating it directly into radiologist workflows to automatically analyze images, flag suspected anomalies, and triage urgent cases within minutes of image acquisition. The deployment specifically includes Aidoc's incidental pulmonary embolism (iPE) algorithm to surface findings that radiologists focused on other regions might otherwise overlook.

Results

Aidoc's iPE algorithm now flags an average of 200 incidental pulmonary embolism cases per month, enabling faster triage and appropriate patient management. Clinical analysis of the Everlight deployment showed read time reductions of nearly 10% for hemorrhagic stroke cases and nearly 12% for pulmonary embolism cases, improving both reporting turnaround and disease awareness for radiologists.

Key Takeaways

  • Deploying AI as a background triage layer in teleradiology workflows enables urgent case prioritization without disrupting the reporting process.
  • Incidental finding algorithms provide measurable safety value beyond their primary use case, catching acute conditions on non-dedicated studies.
  • Early adoption (2019) allowed Everlight to build operational experience with AI-assisted reporting ahead of NHS-wide capacity pressure.

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Vendor

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Details

Company Size
MidMarket
Quality
Curated
Last verified
Jul 28, 2026

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