Artificial intelligence in critical care nursing: A scoping review

Area of Science:

• Nursing
• Health Informatics
• Artificial Intelligence

Background:

• Artificial intelligence (AI) integration in healthcare is rapidly advancing.
• AI offers enhanced patient monitoring and clinical decision-making support in critical care nursing.
• Critical care nursing faces complex, urgent patient data requiring efficient solutions.

Purpose of the Study:

• To synthesize literature on AI applications in critical care nursing.
• To evaluate AI's impact on patient outcomes and nursing practice.

Main Methods:

• Scoping review following Arksey and O'Malley's framework.
• Systematic search across seven electronic databases (PubMed, CINAHL, Embase).
• Included studies focused on AI in critical care nursing or its impact on outcomes/decision-making.

Main Results:

• Thirty-five studies identified six AI application domains: monitoring, intervention, decision support, documentation, resource allocation, and predictive analytics.
• Predictive analytics, especially for complications like sepsis, was most prevalent.
• AI-driven documentation and resource allocation tools showed potential for reducing burden and optimizing workflow.

Conclusions:

• AI has significant potential to enhance critical care nursing practice.
• Implementation challenges require standardized strategies and clear guidelines.
• Balancing technological advancement with human expertise is crucial for AI integration.