ADVANCING ARTIFICIAL INTELLIGENCE-DRIVEN CLINICAL DECISION SUPPORT SYSTEMS TO ENHANCE NURSING PRACTICE AND IMPROVE PATIENT SAFETY IN ACUTE CARE SETTINGS

Abstract

Artificial intelligence (AI)-driven clinical decision support systems (CDSSs) are increasingly transforming healthcare delivery by providing nurses with timely, data-informed recommendations for clinical assessment, risk identification, and patient management. However, their integration into acute care settings remains challenging due to concerns regarding accuracy, interpretability, workflow compatibility, and nurses’ trust in automated recommendations. This study aims to examine how AI-driven CDSSs can enhance nursing practice and improve patient safety in acute care environments. A quantitative, cross-sectional research design was employed using a structured questionnaire administered to nurses working in acute care settings. The instrument assessed perceived usefulness, accuracy, interpretability, ease of use, organizational readiness, clinical decision-making, and patient-safety outcomes. Descriptive statistics, correlation analysis, and multiple regression were used to examine relationships among the study variables. The findings indicate that AI-driven CDSSs can positively support nursing decision-making, particularly by facilitating early identification of patient deterioration, reducing information-processing burden, improving clinical prioritization, and promoting timely interventions. Perceived accuracy and usefulness emerged as important predictors of nurses’ acceptance and effective utilization of AI-supported recommendations, while interpretability and organizational readiness strengthened confidence in system-generated decisions. The study concludes that AI-driven CDSSs can complement, rather than replace, professional nursing judgment when appropriately integrated into clinical workflows. Effective implementation requires user-centered system design, staff training, transparent AI outputs, data-quality safeguards, and organizational support. The findings highlight the potential of responsible AI integration to strengthen nursing practice, enhance clinical decision-making, and improve patient safety in acute care settings.