Artificial Intelligence in the Canadian Healthcare System: Scaling From Novelty to Utility

Area of Science:

• Health Informatics
• Artificial Intelligence
• Healthcare Systems

Background:

• Canada has achieved AI development milestones but needs to focus on responsible and ethical adoption.
• The quintuple aim (enhanced patient and clinician experience, improved health outcomes, lower costs, and equity) is a key goal for AI in healthcare.
• AI in healthcare presents both significant opportunities for benefit and risks of harm.

Purpose of the Study:

• To discuss the current state and future needs of artificial intelligence for healthcare in Canada.
• To explore key themes bridging AI development and responsible adoption.
• To highlight the importance of partnerships and interdisciplinary collaboration.

Main Methods:

• Discussion of three key themes: datasets, generalizability and equity; efficiency and evaluation; and system-focused approaches.
• Inclusion of perspectives from patients, providers, and educators.
• Analysis of Canada's progress and needs in AI for healthcare.

Main Results:

• Identified critical areas for advancing AI in healthcare, including data strategies, ensuring equity, and robust evaluation methods.
• Emphasized the need for a system-level perspective over a product-centric approach.
• Highlighted the essential role of partnerships and interdisciplinary teamwork.

Conclusions:

• Canada possesses the foundational elements and shared values to prioritize beneficial AI adoption in healthcare.
• Responsible AI implementation can improve health and well-being across diverse Canadian populations.
• A concerted effort is needed to shift the balance towards maximizing AI benefits while mitigating risks.