Establishing organizational AI governance in healthcare: a case study in Canada

Summary

This 2024 PMC research study provides a rare, ground-level look at how healthcare organizations actually implement AI governance frameworks in practice. Unlike theoretical governance models, this case study follows Canadian healthcare institutions through the messy realities of establishing oversight structures, managing FDA-authorized medical devices, and balancing innovation with patient safety. The research offers concrete insights into organizational change management, stakeholder alignment, and the unique regulatory challenges facing healthcare AI deployments in Canada's publicly-funded system.

The real-world implementation story

Most AI governance resources tell you what to do—this study shows you how organizations actually do it. The researchers followed healthcare institutions as they navigated competing priorities: IT departments pushing for rapid AI adoption, clinical staff concerned about workflow disruption, and compliance teams grappling with evolving regulatory requirements. The case study reveals the hidden complexities of healthcare AI governance, from managing vendor relationships for FDA-authorized devices to coordinating between provincial health authorities and federal AI research funding requirements.

Key organizational lessons learned

The study identifies three critical success factors that emerged from the Canadian healthcare context. First, governance structures need dedicated clinical champions who can bridge the gap between technical AI capabilities and patient care workflows. Second, organizations must establish clear escalation pathways for AI-related incidents that account for both clinical and data governance protocols. Third, successful implementations create "governance sandboxes" where teams can pilot AI tools under controlled conditions before full deployment. The research also highlights how Canada's significant government investment in AI research (mentioned in the study context) creates both opportunities and compliance obligations for healthcare organizations.

Navigating the regulatory maze

Healthcare AI governance in Canada operates within a complex web of federal and provincial regulations, made more challenging by the increasing use of FDA-authorized medical devices in Canadian hospitals. This study documents how organizations develop internal processes to evaluate these devices while ensuring compliance with Health Canada requirements. The researchers provide specific examples of documentation frameworks, risk assessment protocols, and cross-border regulatory coordination that prove essential for healthcare AI governance.

Who this resource is for

• Healthcare CIOs and IT directors implementing AI governance structures in hospitals or health systems
• Compliance officers in healthcare organizations navigating AI-related regulatory requirements
• Clinical leaders and medical directors responsible for overseeing AI tool adoption in patient care settings
• Healthcare consultants and advisors supporting AI governance implementations across multiple organizations
• Policy researchers and academics studying practical AI governance applications in regulated industries
• Healthcare AI vendors seeking to understand organizational procurement and governance processes

Watch out for: Context limitations

While this case study offers valuable practical insights, remember that it reflects the specific context of Canada's healthcare system in 2024. The governance challenges around publicly-funded healthcare, federal-provincial jurisdiction splits, and Canada's particular approach to AI research funding may not directly translate to other healthcare systems. Additionally, the rapid pace of AI development means some of the specific regulatory considerations around FDA-authorized devices may evolve quickly. Use this study's organizational and change management insights more broadly, but validate the specific regulatory guidance against current requirements in your jurisdiction.