Using AI in healthcare education: a rapid review and commentary

Area of Science:

• Healthcare Education
• Artificial Intelligence
• Educational Technology

Background:

• Artificial intelligence (AI) is increasingly integrated into healthcare and rehabilitation education.
• AI offers potential for personalized learning, adaptive assessment, and simulation-based training.
• Current research explores AI's role in enhancing competency, critical thinking, and learner engagement.

Purpose of the Study:

• To provide a rapid review and commentary on AI's integration into healthcare curricula.
• To highlight AI's potential benefits and challenges in educational settings.
• To emphasize strategies for successful and ethical AI implementation.

Main Methods:

• Rapid review of current research on AI in healthcare education.
• Commentary on findings regarding AI's impact on learners and educators.
• Analysis of ethical, cultural, and pedagogical considerations.

Main Results:

• AI can personalize instruction, facilitate clinical reasoning, and reduce student burdens.
• Ethical challenges include algorithmic bias, data privacy, and inequitable access.
• Rehabilitation education faces specific issues like patient confidentiality and assessment authenticity.

Conclusions:

• Successful AI integration necessitates proactive strategies focused on ethical practice, equity, and reflective learning.
• Embedding AI literacy, cultural humility, and ethical guardrails is crucial.
• AI should complement, not compromise, the humanistic aspects of healthcare practice.