Linking AI for Intervention Strategies: A systematic Review for Nursing

Fascia, Michael

Abstract

Artificial intelligence (AI) has revolutionized many industries, with healthcare atthe forefront. AI-driven predictive analytics holds significant potential for earlyintervention in nursing management, promising enhanced patient outcomes.This paper evaluates AI-driven predictive analytics in nursing by examining itscurrent state, advancements, benefits, and challenges. Peer-reviewed articlesfrom 2018 to 2024 reveal that AI models improve nurses’ ability to identifyat-risk elements, optimize resource allocation, and initiate timely interventions,reducing hospital-acquired infections, readmission rates, and improving patientsafety. Challenges include data quality issues, the need for specialized training,and ethical considerations. This systematic review aims to inform healthcareprofessionals about the potential of predictive analytics to revolutionize earlyintervention strategies.

Citation

Fascia, M. (2024). Linking AI for Intervention Strategies: A systematic Review for Nursing. EMRI Journal of Business Philosophy, 2,

• Journal Article Type: Article
• Acceptance Date: Jul 19, 2024
• Publication Date: 2024
• Deposit Date: Jul 21, 2024
• Publicly Available Date: Mar 26, 2025
• Print ISSN: 2632-3958
• Electronic ISSN: 2632-3966
• Publisher: Edinburgh Multicultural Research Institute
• Peer Reviewed: Peer Reviewed
• Volume: 2
• Keywords: Artificial Intelligence, Predictive Analytics, Nursing Management, Early Intervention, Healthcare Technology, Patient Outcomes, Risk Assessment, AI in Healthcare, Data Quality, Ethical Considerations
• Public URL: http://researchrepository.napier.ac.uk/Output/3738757
• Publisher URL: http://www.soejournal.com/index.php/JBF/article/view/62