Solution Overview
Emergency Department Triage AI
Clinical AI that helps emergency teams triage faster and more consistently — flagging high-risk patients at the front door, before they deteriorate.
The triage challenge in the emergency department
Emergency departments face rising volumes, crowding, and staffing pressure. Triage — the first and most important sorting decision — happens fast and with limited data. Inconsistent acuity scoring leads to under-triage of sick patients and longer waits, contributing to higher left-without-being-seen (LWBS) rates and avoidable risk.
How AI improves emergency triage
KATE, Mednition’s clinical AI, brings machine learning to the triage desk. It reads structured intake data and free-text nursing notes, compares them against patterns from millions of prior visits, and recommends an acuity level in real time. This helps nurses catch high-risk presentations — including early sepsis — that can look deceptively stable.
- Lower left-without-being-seen (LWBS) rates
- Reduced emergency department length of stay
- Increased throughput and capacity
- Earlier sepsis recognition at triage
Built for nurses, inside existing workflows
KATE adds no new screens and requires no workflow changes. It supports the nurse’s judgment rather than replacing it, and its early sepsis model holds FDA Breakthrough Device Designation.