AInception—Optimizing Emergency Planning

The Challenge

The CHUM’s AInception project aims to manage the patient flow between the emergency department (ED) and the care units more proactively and efficiently, by basing decisions on quantified and qualified predictions of ED traffic. AI will be used to predict a visitor’s patient trajectory from triage to discharge from the emergency department to home or another care unit. This solution will allow proactive daily resource management, as well as work upstream for weekly planning of staffing and other resources.



Scale AI investment


Total investment


“CHUM’s objective is to develop, experiment, implement and measure the value of AI, in a collaborative approach, to integrate it into its practices as long as it is relevant and creates value. AInception aims to improve operational efficiency by optimizing resource planning, resulting in less stress and workload for clinical teams and a reduced waiting time in emergency rooms.”

— Anne Nguyen, Chief Health Data Officer, CHUM
Made possible through the
financial support of
Gouvernement du Québec
Gouvernement du Canada

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