Artificial Intelligence Technologies Supporting Nurses' Clinical Decision-Making: A Systematic Review.

Journal: Journal of clinical nursing
Published Date: Nov 25, 2025

Abstract

BACKGROUND: The use of technology to support nurses' decision-making is increasing in response to growing healthcare demands. AI, a global trend, holds great potential to enhance nurses' daily work if implemented systematically, paving the way for a promising future in healthcare. OBJECTIVES: To identify and describe AI technologies for nurses' clinical decision-making in healthcare settings. DESIGN: A systematic literature review. DATA SOURCES: CINAHL, PubMed, Scopus, ProQuest, and Medic were searched for studies with experimental design published between 2005 and 2024. REVIEW METHODS: JBI guidelines guided the review. At least two researchers independently assessed the eligibility of the studies based on title, abstract, and full text, as well as the methodological quality of the studies. Narrative analysis of the study findings was performed. RESULTS: Eight studies showed AI tools improved decision-making, patient care, and staff performance. A discharge support system reduced 30-day readmissions from 22.2% to 9.4% (p = 0.015); a deterioration algorithm cut time to contact senior staff (p = 0.040) and order tests (p = 0.049). Neonatal resuscitation accuracy rose to 94%-95% versus 55%-80% (p < 0.001); seizure assessment confidence improved (p = 0.01); pressure ulcer prevention (p = 0.002) and visual differentiation (p < 0.001) improved. Documentation quality increased (p < 0.001). CONCLUSIONS: AI integration in nursing has the potential to optimise decision-making, improve patient care quality, and enhance workflow efficiency. Ethical considerations must address transparency, bias mitigation, data privacy, and accountability in AI-driven decisions, ensuring patient safety and trust while supporting equitable, evidence-based care delivery. IMPACT: The findings underline the transformative role of AI in addressing pressing nursing challenges such as staffing shortages, workload management, and error reduction. By supporting clinical decision-making and workflow efficiency, AI can enhance patient safety, care quality, and nurses' capacity to focus on direct patient care. A stronger emphasis on research and implementation will help bridge usability and scalability gaps, ensuring sustainable integration of AI across diverse healthcare settings.

Authors

  • Kristina Mikkonen
    Research Unit of Health Science and Technology, University of Oulu, Oulu, Finland; Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland. Electronic address: [email protected].
  • Saara Tuunainen
    Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland.
  • Anne Oikarinen
    Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland.
  • Miia Jansson
    Research Group of Medical Imaging, Physics and Technology, University of Oulu, Oulu University Hospital, Oulu, Finland. Electronic address: [email protected].
  • Brigitte Woo
    Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Wentao Zhou
    Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Toronto, Canada.
  • Wilson Tam
    Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
  • Anna-Maria Tuomikoski
    Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland.
  • Pirjo Kaakinen
    Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland.
  • Jonna Juntunen
    Research Unit of Health Sciences and Technology, University of Oulu, Research Unit of Nursing Science and Health Management, Faculty of Medicine, P.O. Box 5000, FI- 90014, Finland. Electronic address: [email protected].
  • Erika Jarva
    Research Unit of Health Sciences and Technology, University of Oulu, Research Unit of Nursing Science and Health Management, Faculty of Medicine, P.O. Box 5000, FI- 90014, Finland. Electronic address: [email protected].

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