Learning to Teach AI: Understanding the Needs of Healthcare Professionals.

Area of Science:

• Medical Informatics
• Healthcare Education
• Artificial Intelligence in Medicine

Background:

• Artificial Intelligence (AI) is increasingly integrated into clinical settings to improve patient care.
• Healthcare professionals (HCPs) need specialized training to responsibly utilize AI technologies.
• Existing AI education for HCPs may have gaps in addressing practical application and comprehensive knowledge.

Purpose of the Study:

• To explore the informational needs of HCPs regarding AI in clinical practice.
• To identify gaps in current AI educational programs for healthcare professionals.
• To inform the development of effective AI training for HCPs.

Main Methods:

• A qualitative study employing semi-structured interviews with educators and learners from AI programs.
• Inductive thematic analysis of interview data to identify key themes.
• Exploration of informational needs and educational gaps related to AI in healthcare.

Main Results:

• Three primary themes emerged: the necessity of a longitudinal AI curriculum, the importance of an active learning approach, and the value of a multidisciplinary approach to curriculum design.
• Identified needs include transforming provider mindset, skillset, and toolset through AI education.
• Fostering knowledge mobilization and optimizing AI tool utilization are crucial for care provision.

Conclusions:

• A comprehensive, longitudinal, and multidisciplinary AI curriculum is essential for preparing HCPs.
• Active learning strategies are vital for effective knowledge mobilization and AI tool application.
• Five key recommendations were developed to equip HCPs with necessary AI skills for the future of healthcare.