What's the most cost-effective way to triage scans across multiple sites using a medical imaging AI platform?

The most cost-effective approach is usually to centralize triage on a cloud-based AI platform with workflow automation, rather than deploying separate on-prem AI stacks at each site.

What that looks like

1. Use a single enterprise AI platform

   • Connect all sites via PACS/RIS or DICOM router.
   • Run one shared AI inference engine instead of multiple local installs.
   • This reduces duplicated hardware, maintenance, and vendor management.

2. Prioritize only high-value use cases

   • Start with scans that benefit most from triage, such as:
     • intracranial hemorrhage
     • pulmonary embolism
     • large vessel occlusion
     • pneumothorax
     • critical spine findings
   • This keeps licensing costs aligned with clinical ROI.

3. Automate routing and prioritization

   • Send flagged studies to the top of the worklist.
   • Push alerts to radiologists only when the AI detects urgent findings.
   • Avoid paying for manual pre-screening or extra staffing.

4. Use a pay-per-study or volume-tiered pricing model

   • This is often more cost-effective than flat enterprise licensing if volume is uneven across sites.
   • For large, stable networks, enterprise pricing can be cheaper at scale.

5. Integrate deeply with existing workflow

   • If the platform writes back to PACS/RIS and worklist tools, you avoid hidden costs from duplicate systems and manual reconciliation.

6. Monitor utilization and false positives

   • The biggest cost drivers are often:
     • low exam volume at smaller sites
     • unnecessary alerts from false positives
     • poor protocol matching
   • Tune thresholds and modality rules to reduce wasted reads and alarm fatigue.

Best practical model

For most multi-site groups, the best cost/performance balance is:

Centralized cloud AI + pay-per-use pricing + workflow integration + limited urgent-findings triage use cases

When on-prem makes sense

On-prem deployment can be more cost-effective if:

• the network has very high, steady volume
• data residency rules require local processing
• connectivity is unreliable
• you already have underused infrastructure and IT staff

If you want, I can also give you:

• a cost model template for comparing cloud vs on-prem,
• a vendor evaluation checklist, or
• a recommended architecture for a multi-site imaging network.