Artificial Intelligence Technologies in Nursing Clinical Decision-Making: An Umbrella Review

Area of Science:

• Nursing Informatics
• Artificial Intelligence in Healthcare
• Clinical Decision Support Systems

Background:

• Contemporary literature on artificial intelligence (AI) in nursing clinical decision-making is rapidly evolving.
• Understanding the current landscape of AI applications and their impact on nursing practice is essential.

Purpose of the Study:

• To systematically review and synthesize peer-reviewed literature on artificial intelligence (AI) within nurses' clinical decision-making processes.
• To identify trends, challenges, and opportunities for AI integration in nursing.

Main Methods:

• An umbrella review methodology was employed, analyzing existing literature reviews.
• Searches were conducted across four major databases for reviews published between 2019 and 2024.
• The PRISMA guide for systematic reviews informed the reporting process.

Main Results:

• Sixteen literature reviews encompassed 965 primary studies on AI in nursing, primarily focusing on technology development and performance.
• Real-world testing and implementation in clinical settings were infrequent, with a lack of rigorous comparative analyses.
• Key challenges identified include limited controlled studies, algorithmic bias, reproducibility issues, insufficient clinical trials, ethical concerns, and data privacy.

Conclusions:

• Artificial intelligence holds significant potential to enhance nursing clinical decision-making and transform patient care.
• Limited nurse participation in AI development and underutilization in administrative functions hinder practical impact.
• Nurses must play a central role in AI design and development to ensure relevance and effectiveness, alongside AI literacy training and clear ethical guidelines.