.png)
HeroAI
Healthcare · Canada
55% shorter wait times
HeroAI cuts paediatric ER wait times by 55% with AI-driven triage at SickKids Toronto
200+ hours of ER capacity freed. AI classifies urgency in real time. Built on Azure OpenAI.
Friction
Paediatric psychiatric emergencies at SickKids Toronto waited 6 to 8 hours for a psychiatry consultation decision, unnecessarily occupying ER capacity while other patients waited.
Breakthrough
Real-time AI triage that classifies patient urgency from first assessment data, so clinicians can validate an AI-suggested classification rather than analyse everything from scratch.
Impact
55% reduction in patient wait times. 200+ hours of ER capacity freed per year. 98.9% alignment between AI assessment and live clinical diagnosis.
Unlock the full analysis with breakthrough, impact, what made it smart and its technical approach below!
Problem
Paediatric psychiatric emergencies at SickKids Toronto waited 6 to 8 hours for a consultation decision, tying up ER capacity unnecessarily while other patients waited.
What made it smart
The clinical knowledge hub: an AI-searchable database of prior cases that lets clinicians find relevant precedents in natural language. Combined with real-time triage classification, this accelerates both the decision and the confidence in it.
Technical approach
Platform on Microsoft Azure. Real-time ML using vital signs, symptoms, and anamnesis history. Algorithm on Azure AI Foundry and Azure OpenAI Service. Clinician receives AI-suggested urgency classification for validation. Knowledge hub with AI-driven search.
Strategic lesson
AI in acute care creates most value when it accelerates clinical judgment, not replaces it, but gives clinicians the right input faster.
Reflection question
Where do your most skilled people spend the most time on decisions that are actually routine? What would they do with that time if AI handled the classification?