Comparison of an AI-Based Self-Triage System with Traditional Physical Triage Methods
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By
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Maaike Wempe
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Frits Holleman
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Michiel Schinkel
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Michiel Gorzeman
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October 1, 2026
Clinical Scorecard: Comparison of an AI-Based Self-Triage System with Traditional Physical Triage Methods
At a Glance
| Category | Detail |
|---|
| Condition | Emergency Triage |
| Key Mechanisms | AI self-triage using dynamic algorithms to assess urgency and recommend care pathways. |
| Target Population | Adults presenting to the emergency department. |
| Care Setting | Emergency Department |
Key Highlights
- AI self-triage may standardize triage processes and reduce workload for ED personnel.
- Urgency classifications from AI were compared to those from the Dutch NTS.
- AI triage is currently unsuitable for widespread implementation.
- Physical triage relies on clinical judgment and can lead to misclassification of urgency.
Guideline-Based Recommendations
Diagnosis
- Urgency classifications should be validated against clinical outcomes.
Management
- AI triage programs should undergo continuous review and validation by medical experts.
Monitoring & Follow-up
- Assess agreement between AI triage outputs and clinical diagnoses at ED discharge.
Risks
- Potential for overtriage and undertriage in AI classifications compared to traditional methods.
Patient & Prescribing Data
Adults presenting to the ED, excluding those arriving by ambulance or with language barriers.
AI triage provides tailored recommendations based on urgency classifications.
Clinical Best Practices
- Incorporate AI triage as a supplementary tool rather than a replacement for physical triage.
- Ensure AI systems are certified and comply with relevant regulations.
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