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Triage is the highest-stakes decision in clinical operations. AI triage augments clinician judgment with real-time acuity scoring — never replacing it.
Manual triage relies on individual clinician experience and verbal patient descriptions. AI triage standardises the signal: structured intake captures symptoms in the patient's own words, vitals integrate from on-site devices, and an acuity score surfaces in real-time for the triage nurse to validate.
Patient describes symptoms in their own words, in their own language. NLP captures structured ICD-10/SNOMED-CT clinical coding for the triage nurse.
On-site BP, pulse-ox, temperature devices feed into the triage scoring engine in real-time.
AI-derived acuity score (Manchester / ESI / CTAS-aligned) presented as decision-support to the triage nurse. Score, confidence, and contributing factors all visible.
High-acuity patients route to acute care; low-acuity to standard queue. Configurable per-clinic.
Every triage decision logged with AI signal, nurse override (if any), and final disposition. Audit-ready for clinical-operations review.
AI triage is decision-support, never replacing clinician judgment. Triage nurse can override at any point; override reasons captured for continuous improvement.
Triage time per patient cut from 8 minutes to 2 minutes
Acuity-score agreement with senior nurse > 90% in production
Audit-pass rate 100% on triage-decision review
Multi-language support handles diverse patient demographics
AI triage runs as a real-time inference service. Patient intake (NLP) feeds a trained acuity classifier; vitals from device integration update the score continuously. The model is calibrated against historical triage outcomes per facility within 30-60 days of go-live. Every decision has a model card, evaluation harness, and human-oversight path.
No. AI triage is decision-support. The triage nurse validates, overrides if needed, and makes the final disposition.
After calibration, agreement with senior triage nurses exceeds 90% in production. Where AI and nurse disagree, the nurse decides; the disagreement is logged for continuous improvement.
Population-specific calibration available. Default models handle adult acuity; paediatric and obstetric modules add specialty-specific scoring.
In most jurisdictions, decision-support AI falls below the medical-device threshold. Where it would be regulated, we work with the customer's regulatory affairs team on the appropriate pathway.
Yes. Every model has a documented model card, evaluation harness, and audit log of every decision. Available for inspection under NDA.
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