OntarioMD (OMD) has introduced an updated online Privacy and Security Training for the Healthcare Sector, specifically tailored to address the increasing use of Artificial Intelligence (AI) by clinicians. The redesigned course offers practical guidance and resources for safely integrating AI tools into medical practice.
Addressing Administrative Burden with AI
Dr. Chandi Chandrasena, Chief Medical Officer of OntarioMD, noted that administrative burden remains a major challenge, particularly for family physicians. While clinicians are eager to explore technologies that can reduce paperwork, they must ensure patient privacy and regulatory compliance. AI scribes, which generate clinical notes during patient visits, show promise in alleviating documentation tasks, allowing physicians to focus more on patient care.
Comprehensive Course Content
The training covers key privacy and cybersecurity concepts for clinicians in community and hospital settings. Topics include Ontario's Personal Health Information Protection Act (PHIPA), the obligations of Health Information Custodians (HICs), best practices for protecting personal health information (PHI), legal and professional responsibilities when using AI tools, and real-world cybersecurity scenarios.
Growing Concerns About AI Risks
A recent survey by the Canadian Medical Association and the Canadian Federation of Independent Business found that 49% of respondents cited medico-legal and privacy risks as their primary concern regarding AI scribe adoption. Ariane Siegel, General Counsel & Chief Privacy Officer of OMD, emphasized that understanding privacy, security, and governance requirements is crucial for using AI in clinical settings.
Encouraging Safe Adoption
OMD encourages physicians, nurse practitioners, and clinic teams to complete the training before adopting AI-enabled technologies. The course aims to prepare healthcare professionals to use these innovations responsibly.
Clinician Feedback
Dr. Loredana D., a family physician, praised the training, stating it removes the guesswork from integrating new AI tools safely into practice, making it relevant and aligned with current clinical realities.
