Fraser Health named runner-up in Gartner awards

SURREY, BC – At Fraser Health, the Centre for Advanced Analytics, Data Science and Innovation (CAADSI) has developed an AI-enabled decision-support platform that’s designed for reuse across clinical and operational contexts, rather than building isolated point solutions. This work was recognized as a Runner-Up in the 2025 Gartner Eye on Innovation Awards, reflecting a broader shift toward treating AI as a scalable system capability rather than standalone use cases.

“What made this work different was not just the technology – it was how we brought people together around a shared purpose,” said Dr. Dimple Prakash (pictured left), interim executive director at CAADSI. “By combining frontline clinical expertise, data science, and a strong consulting mindset, we were able to co-create solutions that are both practical and scalable. That partnership is what ultimately enables real, lasting impact.”

The initiative was grounded in frontline decision-making needs, including reducing clinician burden, preserving autonomy, and enabling earlier, more proactive actions.

In-house machine learning models generate daily patient demand forecasts with approximately 90% accuracy, providing visibility into anticipated surges and flow pressures.

To translate insight into action, Fraser Health introduced an AI-enabled “what-if” scenario simulator. The tool enables physicians and operational leaders to test scheduling and resourcing strategies, assess alignment with projected demand, and evaluate impacts on patient flow and wait times, augmenting existing systems while maintaining clinician control.

“The real shift is moving from AI as a prediction tool to AI as a decision intelligence engine,” said Dr. Casper Shyr (pictured right), senior director of advanced analytics and data science at CAADSI. “By integrating probabilistic demand forecasting, scenario simulation, and scheduling optimization into a unified platform, we enable teams to model scenarios, quantify trade-offs, and understand system-wide impacts before decisions are made.”

While initially focused on physician scheduling and patient flow, the work has evolved into an AI-enabled decision intelligence platform that integrates surge forecasting, workforce simulation, patient trajectory modelling, and funding scenario analysis within a single framework. The platform supports operational planning, scenario testing, quality risk monitoring, and system-level simulations, including funding and policy decisions.

Early results indicate measurable improvements, including up to a 50% reduction in wait times, two to three hours saved per physician per week (approximately 20,000 hours annually), and improved predictability in staffing and patient flow. These outcomes highlight that impact is driven not only by predictive accuracy, but by embedding AI into clinical and operational workflows.

As healthcare continues to invest in AI, the challenge is no longer adoption, but scale. The experience at Fraser Health suggests that success depends on building capabilities that integrate directly into decision-making processes. With this shift, AI can move beyond isolated pilots toward sustained, system-wide impact.