Artificial intelligence for improved patient flow management

The Network is currently undertaking a project to evaluate the potential of artificial intelligence in patient flow management.

Led by the Health Analytics and Predictive Intelligence team, in collaboration with the Research Chair in Artificial Intelligence in Health at the Université de Moncton, this project aims to better predict the probable length of hospital stays.

Its purpose is to use Network data securely and confidentially to develop a decision-support tool for clinicians, managers and patient flow teams.

Optimized planning helps avoid wasted time, reduce bottlenecks and improve patient flow. Ultimately, this approach helps to reduce access times, particularly in emergency departments, while maintaining quality and safety of care.

Patient flow initiatives are designed to provide the right care, at the right time, in the right place, while ensuring safe occupancy levels and facilitating transitions to appropriate care settings. With this in mind, several projects have been rolled out in the four zones to improve discharge processes, reduce length of stay and preserve patient autonomy.

The average occupancy rate of our facilities has fallen from 105% to 95% in recent months through these efforts.