AI in the Health Sector: Systematic Review of Key Skills for Future Health Professionals

Area of Science:

• Health Informatics
• Medical Artificial Intelligence
• Digital Health

Background:

• Technological advancements are transforming healthcare with digital solutions.
• Artificial intelligence (AI) offers significant potential in diagnostics, data analysis, and personalized medicine.
• A gap exists in literature and training for AI competencies among healthcare professionals.

Purpose of the Study:

• To systematically review and consolidate essential skills for healthcare professionals integrating AI into clinical practice.
• To identify the current state of literature regarding AI competencies in healthcare.

Main Methods:

• Systematic review of peer-reviewed literature from PubMed, Scopus, and Web of Science (2018 onwards).
• Inclusion of studies focusing on specific skills/training for AI integration in healthcare.
• Bias evaluation using Cochrane's recommendations.

Main Results:

• Seven studies met inclusion criteria from an initial 2457 articles.
• Identified 14 key skill areas for AI integration, including AI fundamentals, data analytics, and ethical considerations.
• AI fundamental knowledge focuses on algorithm assessment rather than technical programming skills.

Conclusions:

• A significant gap in focused research on AI competencies for healthcare professionals persists.
• Regulatory bodies play a crucial role in AI adoption and trust.
• Essential competencies include AI fundamentals, data analysis, ethical/legal considerations, and maintaining compassionate patient care alongside AI integration.