Developing a Canadian artificial intelligence medical curriculum using a Delphi study

Area of Science:

• Medical Education
• Artificial Intelligence in Healthcare
• Curriculum Development

Background:

• Integrating artificial intelligence (AI) education into medical curricula is essential for preparing future healthcare professionals.
• There is a growing need for medical professionals to understand and utilize AI technologies in clinical practice.
• Canadian undergraduate medical education requires a structured approach to AI competency development.

Purpose of the Study:

• To establish an expert-based artificial intelligence (AI) curriculum for Canadian undergraduate medical students.
• To identify essential AI learning competencies for medical education.
• To provide recommendations for integrating AI competencies into existing medical curricula.

Main Methods:

• The Delphi method was employed to achieve consensus among experts.
• A panel of 18 Canadian experts in health and AI participated in three survey rounds.
• Key curricular components were identified across ethics, law, theory, application, communication, collaboration, and quality improvement.

Main Results:

• Substantial support exists among medical educators and professionals for comprehensive AI education.
• 82 out of 107 identified curricular competencies were deemed essential for clinical and educational priorities.
• The study identified key areas for AI competency development in medical students.

Conclusions:

• The developed AI curriculum provides a framework for enhancing AI literacy among medical students.
• The endorsed competencies will equip future healthcare professionals to effectively use AI technologies.
• Integrating AI education is crucial for advancing healthcare quality and innovation.