AI-Powered Medical Imaging Triage

Implement AI triage for radiology workflows — automatically prioritising urgent findings and flagging critical abnormalities for immediate review.

HealthcareAdvanced4-8 months

Transformation

Before & After AI

What this workflow looks like before and after transformation

Before

Radiology reads are processed first-in-first-out regardless of urgency. Critical findings (stroke, pneumothorax, fractures) can wait hours in the queue. Radiologists spend significant time on normal studies while urgent cases wait. Turnaround time for emergency reads averages 2-4 hours.

After

AI pre-screens every imaging study within minutes of acquisition, flagging critical findings and automatically reprioritising the worklist. Radiologists see urgent cases first, reducing critical finding turnaround to under 30 minutes. AI also flags incidental findings that might otherwise be missed.

Implementation

Step-by-Step Guide

Follow these steps to implement this AI workflow

1

Define Clinical Priorities

2 weeks

Work with radiology and emergency medicine leadership to define which findings trigger AI triage escalation. Establish clinical validation requirements and regulatory pathway (FDA clearance, local health authority approval).

2

Select & Validate AI Models

6 weeks

Evaluate FDA-cleared / CE-marked AI imaging solutions for your priority conditions. Run retrospective validation on your historical imaging data to confirm performance in your patient population. Document sensitivity, specificity, and processing time.

3

Integrate With PACS & Worklist

4 weeks

Connect AI models to your PACS (Picture Archiving and Communication System) for automatic study ingestion. Build worklist integration so AI priority scores reorder the radiologist queue. Implement notification system for critical findings.

4

Clinical Pilot

6 weeks

Run AI triage in parallel with standard workflow — AI flags studies but radiologists process normally. Compare AI flags against final radiologist reports to validate real-world performance. Adjust sensitivity thresholds based on clinical feedback.

5

Go Live & Monitor

2 weeks + ongoing

Activate AI-driven worklist prioritisation. Monitor turnaround times, false positive/negative rates, and radiologist satisfaction. Track patient outcomes for AI-flagged vs. non-flagged studies. Report to clinical governance and quality committees.

Tools Required

FDA-cleared/CE-marked AI imaging modelsPACS with DICOM integrationHL7/FHIR messaging for worklistClinical notification systemPerformance monitoring dashboard

Expected Outcomes

Reduce critical finding turnaround time from 2-4 hours to under 30 minutes

Detect 15-20% more incidental findings that would otherwise be missed

Improve radiologist workflow efficiency by 25-35%

Reduce diagnostic errors for time-sensitive conditions

Meet or exceed quality benchmarks for critical finding communication

Solutions

Related Pertama Partners Solutions

Services that can help you implement this workflow

Frequently Asked Questions

Yes. AI diagnostic tools are classified as medical devices in most jurisdictions. In the US, they need FDA clearance (typically 510(k) pathway). In the EU, CE marking under MDR. In Southeast Asia, requirements vary by country. Using pre-cleared/approved solutions from established vendors simplifies this significantly.

Most mature AI triage solutions cover chest X-ray, head CT, and mammography. Emerging solutions cover MSK (musculoskeletal) imaging, abdominal CT, and cardiac imaging. The key is selecting AI solutions validated for your specific imaging modalities and clinical priorities.

Ready to Implement This Workflow?

Our team can help you go from guide to production — with hands-on implementation support.