Artificial intelligence in critical care nursing: A scoping review.

BACKGROUND

The integration of artificial intelligence (AI) into health care has been rapidly advancing, driven by its potential to enhance nursing care quality through improved decision-making and efficiency. Within critical care nursing, where the complexity and urgency of patient data are paramount, AI technologies offer significant advantages, such as enhanced patient monitoring and support in clinical decision-making.

AIM/OBJECTIVE: The aim of this scoping review was to synthesise existing literature on AI applications in critical care nursing and their impact on patient outcomes and nursing practice.

METHODS

Following Arksey and O'Malley's framework, we conducted a systematic search across seven electronic databases including PubMed, CINAHL, and Embase. Studies were included if they involved AI applications in critical care nursing or reported on AI's impact on patient outcomes and clinical decision-making in critical care settings. A synthesis of the literature was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews checklist.

RESULTS

Thirty-five studies that addressed this topic were included. The review identified six distinct domains of AI applications: monitoring, nursing intervention, clinical decision support systems, documentation, resource allocation, and predictive analytics. Predictive analytics emerged as the most prevalent application, particularly in forecasting complications such as pressure injuries and sepsis onset. Notably, narrowly focussed AI applications demonstrated superior performance compared to broader applications in clinical decision support systems, particularly in specific tasks like neonatal pain classification. AI-driven documentation systems showed promise in reducing administrative burden and improving accuracy, while resource allocation tools enhanced staffing optimisation and workflow management in intensive care units.

CONCLUSIONS

Our findings demonstrate AI's significant potential to enhance critical care nursing practice while highlighting implementation challenges. Future research should focus on developing standardised implementation strategies and clear guidelines for AI integration in nursing workflow while maintaining the balance between technological advancement and human expertise.

REGISTRATION

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