Evidence-based action plan for integrating artificial intelligence in an academic medical centre-a multidisciplinary...

Area of Science:

• Healthcare Innovation
• Medical Education Technology
• Clinical Informatics

Background:

• Artificial intelligence (AI) is increasingly recognized for its potential to improve healthcare delivery globally.
• Integration of AI into clinical practices, education, and research is anticipated, even in resource-limited settings.
• A structured approach is needed to facilitate AI adoption in healthcare.

Purpose of the Study:

• To develop a comprehensive action plan for integrating artificial intelligence (AI) into medical education, research, and clinical practices.
• To utilize the SWITCH model of change, incorporating both rational and emotional aspects of integration.
• To provide a context-specific framework for AI adoption in healthcare.

Main Methods:

• Exploratory qualitative study using reflexive thematic analysis of semi-structured interviews.
• Co-design workshop with academic leaders, healthcare professionals, and medical students.
• Collaborative development of an action plan based on interview and workshop findings.

Main Results:

• Four key themes emerged: AI opportunities, apprehensions, leadership styles for change, and capacity building needs.
• Workshop discussions focused on aligning current AI knowledge with future needs, including clear instructions, motivators, and environmental changes.
• The action plan comprises three domains—strategic actions, change pathway enablement, and environmental readiness/human motivation—with twenty actionable components.

Conclusions:

• A context-specific conceptual action plan was developed for integrating AI into healthcare education, clinical services, and research.
• Further research should focus on pilot implementation and empirical validation of the action plan.
• Assessing the feasibility, effectiveness, and scalability of the proposed AI integration plan across diverse healthcare settings is recommended.