SCALE AI’s AI for Healthcare Initiative: $21 million in investments supporting 9 AI projects for better healthcare in Canada
Today, SCALE AI took the stage at Canada’s ALL IN event to announce investments of $21 million for nine artificial intelligence (AI) projects selected by SCALE AI as part of its AI for Healthcare Initiative to support hospital projects pioneering the deployment of AI solutions. This latest SCALE AI initiative promotes collaboration between hospitals and AI product and solutions providers across the country to innovate further and accelerate the deployment of AI in the Canadian healthcare network to improve operations, logistics and resource allocation.
These projects are supported by funding provided to SCALE AI as part of the Pan-Canadian Artificial Intelligence Strategy, through which the Government of Canada is investing in efforts to drive the adoption of artificial intelligence across Canada’s economy and society.
Led by and deployed into Canadian hospitals, the projects announced today — including optimizing and forecasting for resource and workflow operations, patient care management and virtual triaging and queue management — will help resolve complex challenges in Canadian healthcare. These technological advances will have tangible, measurable effects on hospital activities, notably by helping to improve the patient’s journey and experience by streamlining the logistics, determining daily resource management, or reducing waiting times.
The Honourable François-Philippe Champagne, Canada’s Minister of Innovation, Science and Industry, says: “AI for healthcare offers powerful new solutions to improve the daily lives of Canadian patients. Through the Pan-Canadian Artificial Intelligence Strategy, SCALE AI is working with local AI experts to develop these solutions in partnership with local healthcare institutions and hospitals to ensure better data protection and a solid ethical framework for analyzing and processing information about patients and our healthcare system.”
Julien Billot, CEO, SCALE AI, explains: “SCALE AI is working with many partners to accelerate the rapid adoption and integration of AI in key sectors like healthcare. Through this initiative, AI ecosystem players and hospitals are mobilizing to meet today’s public health challenges and to have a profound effect on healthcare in Canada.”
Hélène Desmarais, Co-Chair of the Board of Directors, SCALE AI, adds: “In partnership with the entire ecosystem, SCALE AI continues to help develop AI in Canada, accelerate its integration into Canadian businesses and support the management and delivery of healthcare through AI.”
“These projects are helping to find efficiencies and optimize limited resources to improve patient well-being.”
– Hélène Desmarais, Co-Chair of the Board of Directors, SCALE AI
AI for Healthcare: 9 projects representing investments of $20.9 million
| → AI-Driven Demand Forecasting for CIUSSS West-Central Logistics Optimization
Partners: CIUSSS West-Central Montreal (CIUSSS-CCOMTL), IVADO Labs SCALE AI investment: $1.5 million Total investment: $2.3 million |
The Integrated University Health and Social Services Network for West-Central Montreal (CIUSSS West-Central Montreal) and its connected health innovation hub – OROT are proud to partner with IVADO LAB in order to co-develop and deploy an Artificial Intelligence System designed to enhance and streamline the logistics of the CIUSSS West-Central warehouse through precise demand forecasting. The partnership is designed to leverage the unique capabilities of both organizations in order to transform the decision-making process to a more informed, data-driven approach, thereby empowering the CIUSSS logistics professionals to make more informed and effective operational decisions. CIUSSS West-Central Montreal is committed to providing healthcare recipients with timely access to a seamless continuum of care across its 34 sites. OROT has a mandate to lead the way in co-creation and interdisciplinary collaboration, with the aim of supporting the creation of digital innovations that meet user needs.
Audrey Benarrosh, Director of Logistics and Procurement of the CIUSSS West-Central Montreal: “We are thrilled to be able to collaborate with IVADO LAB in order to co-create a system capable of accurately predicting material requirements, streamline procurement processes, and ultimately help us bolster the overall operational efficacy and ensure optimal use of resources.” Danina Kapetanovic, Chief Innovation Officer of the CIUSSS West-Central Montreal and Head of OROT: “Understanding the context and data is the compass that guides AI towards its true potential; without them, we navigate blindly, missing the destination of effective solutions. Leveraging its unique skill sets, OROT’s will foster interdisciplinary collaboration between the partners thus ensuring that the resulting solution is user-centric and effective.” |
| → Developing the First Patient-Centric Care Management System for Oncology
Partners: The Ottawa Hospital, The Princess Margaret Cancer Center, The Centre Hospitalier de l’Université de Montréal, Gray Oncology Solutions, The Jewish General Hospital, The Programme Québécois de Cancérologie, The Centre Intégré de Santé et de Services Sociaux de Laval, The McGill University Health Centre (MUHC), The CIUSSS de l’Estrie – Sherbrooke, The Southlake Regional Health Centre, The Canadian Cancer Society SCALE AI investment: $1.9 million Total investment: $2.9 million |
This AI project focuses on developing, deploying, and evaluating software to address three key challenges in oncology: the stochastic nature of patient flow, the difficulty of proactive capacity planning, and the coordination of multiple services that a single patient may require throughout their care trajectory. The project brings together a multi-province consortium of cancer centers and will use multiple algorithmic classes to address each of these challenges. These range from Machine Learning and Statistical Modeling for the prediction of patient flow to Operations Research algorithms that proactively determine the ideal set of resources required to sustain the predicted incoming patient flow.
Melissa Diffey, Manager, Radiation Medicine Program, The Ottawa Hospital: “AI is an integral part of our innovation and development strategy. We believe in the importance of using this tool to improve medical decision-making, and therefore patient care, throughout their life trajectory.” |
| → Optimizing Emergency Department Resources with AI Decision Support Tool
Partners: Unity Health Toronto (St. Joseph’s Health Center, St. Michael’s Hospital), Signal 1, Grand River Hospital SCALE AI investment: $1.5 million Total investment: $3 million |
As the health care system aims to recover from the COVID-19 pandemic, emergency departments (EDs) are experiencing system-wide pressures: patients are coming in sicker; staff turnover has been unprecedented; and patients are experiencing longer wait times before seeing a doctor in the ED and before receiving a hospital bed. Unity Health Toronto is one of Canada’s largest Catholic healthcare networks. It is home to the nation’s only hospital-based applied AI program, which has launched more than 50 AI and analytics tools into clinical practice. The collaborative project between Signal 1 and the hospital partners will provide ED staff with a tool to better manage patient flow. The project will deploy real-time AI systems in a hospital ED to optimize staffing resources, accelerate safe patient discharge and reduce the volume of avoidable hospital admissions. Signal1’s system uses patient charting data to predict the likelihood that a patient can be discharged.
Dr. Muhammad Mamdani, Vice President of Data Science and Advanced Analytics, Unity Health Toronto: “At Unity Health Toronto we are already seeing a tremendous impact and potential for AI to transform healthcare. Our collaboration with Signal 1 is helping to accelerate the development of AI tools that improve hospital efficiency and care outcomes – enhancing the hospital experience for providers and patients alike.” |
| → Emergency Dept AI-Enabled Virtual Triaging and Queue Management Application
Partners: Humber River Health, Deloitte, MEDITECH Collaborative, Mackenzie Health SCALE AI investment: $1.5 million Total investment: $2.4 million |
Humber River Health (HRH) recognizes the opportunity to develop an AI-Enabled Virtual Triaging and Queue Management Application to help navigate patients to the appropriate care at the appropriate time. HRH will apply AI and Machine Learning to forecast and optimize patient queues in the ED, determine the optimal pre-arranged time slot per patient, and dynamically adjust the time slot per patient to continuously optimize and manage the queue of patients using real-time/near-real-time data. The goals are to achieve more efficient use of health system resources, improve patient flow, reduce occurrences of unexpected surges in emergency department (ED) demand, and eventually redirect the volume of non-urgent patients accessing the ED to the most appropriate care.
Barbara Collins, CEO, Humber River Health: “Humber River Health is committed to working with our community and other partners to collectively learn to deliver innovative, safe and equitable healthcare. With one of the busiest Emergency Departments in Ontario, we are continuously leveraging technology to work for staff and physicians, giving them more time to spend with patients, eliminating inefficiencies, and reducing the chance of errors. AI furthers our ability to revolutionize the patient experience and deliver even higher quality care, resulting in a better patient journey from start to finish.” |
| → AInception—Optimizing Emergency Planning
Partners: Centre hospitalier de l’Université de Montréal (CHUM), Moov AI, CIUSSS Estrie – CHU Sherbrooke Scale AI investment: $1.5 million Total investment: $2.3 million |
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.
Anne Nguyen, Chief Health Data Officer, CHUM: “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.” |
| → AI-Based Decision Tool to Forecast, Optimize and Allocate Paramedic Resources
Partners: Urgences-santé, Alberta Health Services – Emergency Medical Services, Emergency Medical Care Incorporated, Airudi, McGill Clinical and Health Informatics SCALE AI investment: $1.5 million Total investment: $2.3 million |
Urgences-santé is Quebec’s only public prehospital emergency service organization. The project aims to equip Urgences-santé with a single AI-powered decision-support tool to improve staffing efficiency in the mid-term, avoid service gaps in the short term and mitigate service gaps in the near term. At the core, the solution will predict the demand for emergency care at these horizons, and propose solutions for maintaining target levels of service while reducing costs.
Patrick Taillefer, Deputy Director, Strategy and Performance and Research, Urgences-santé: “With the help of AI, Urgences-santé will be able to better deliver timely paramedic care to 2.5M people over a 744 km2 area, 24 hours a day, 365 days a year.” |
| → AI-Driven Physician Scheduling Solution and Workflow Optimization
Partners: Fraser Health Authority, Deloitte SCALE AI investment: $1.5 million Total investment: $2.2 million |
Fraser Health Authority and Deloitte are co-leading this AI project, with Burnaby Hospital and Eagle Ridge Hospital as the pilot sites for this initiative. This project seeks to leverage AI/ML-based solutions to resolve complex challenges facing the human resources supply chain for the FHA ecosystem, with an initial focus on the Emergency and Hospital Medicine departments. AI will enable accurate demand forecasting, optimization and simulation modelling of physician scheduling to achieve decreased workload, increased job satisfaction, shorter wait times, and improved patient experiences.
Jennifer MacGregor, Vice President, Digital Patient and Provider Experience, Fraser Health Authority: “In this partnership, we are focusing on leveraging AI technology to improve our Health Human Resource scheduling and capacity planning. To begin, the AI model will support our physician scheduling activities at two of our twelve hospitals. We are excited about this partnership with Scale AI and Deloitte to embark on innovative solutions which will improve access to care for those we serve.” |
| → Resource Optimization Chart for Pediatric Intensive Care
Partners: Centre Hospitalier Universitaire Sainte-Justine, Montreal Children’s Hospital, IVADO Labs SCALE AI investment: $1.5 million Total investment: $1.8 million |
CHU Sainte-Justine (CHUSJ) stands as Quebec’s sole healthcare institution solely committed to the care of children, teenagers, and mothers. This project’s solution features a dashboard oriented towards situation analysis. Utilizing AI technology, it enables more precise staff allocation by leveraging patient data and forecasting potential new admissions. It effectively calculates staffing needs and optimizes the allocation of patient beds within the pediatric intensive care unit, ensuring a well-balanced workload for the staff.
Philippe Jouvet MD PhD, clinical researcher, CHU Sainte-Justine : “Advances in medical science and technology have never had so much to contribute to human health, thanks in particular to the use of artificial intelligence, which opens many new avenues in the management of patients’ health and clinical services.” |
| → Improvement of Radiation Therapy Through Staff Scheduling Optimization
Partners: Princess Margaret Cancer Centre, University Health Network, IVADO Labs, Southlake Regional Health Center, eSummit SCALE AI investment: $1.5 million Total investment: $1.7 million |
The Princess Margaret Cancer Center is proposing an AI-based solution to optimize staff scheduling, increase efficiency, and improve staff satisfaction. The solution consists of several components: a workload predictor, an absence predictor, a monthly optimizer, a monthly re-optimizer, and a daily re-optimizer. These components leverage historical data, predict uncertainties, and utilize advanced algorithms to construct robust schedules, minimize operational costs, ensure sufficient coverage, and minimize disruptions to staff and patient schedules.
Philip Wong, Radiation Medicine Associate Director of ambulatory care, UHN Princess Margaret: “Implementing the AI-based solution is intended to positively impact Princess Margaret’s operations, staff satisfaction and patient care continuity. By reducing the time spent on scheduling tasks, team supervisors will hopefully be able to focus on mentoring, quality improvement projects, research, and enhancing the overall quality of care.” |
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