The Role of Artificial Intelligence–Assisted Clinical Decision Support Systems in Enhancing Nursing Practice and Patient Outcomes in Iraqi Hospitals

Abstract

Clinical decision support systems (CDSSs) augmented by artificial intelligence (AI) are revolutionising modern health care, but little is known about their use in Iraqi tertiary hospitals. Nurses are the primary decision-makers in clinical practice, and poor decision support can pose a patient safety risk. Objective: The aim of this study was to compare the effectiveness of AI-supported CDSS with traditional (non-AI) methods in improving nursing practice and certain patient outcomes in tertiary hospitals in three Iraqi governorates. Methods: A prospective, comparative, cross-sectional design was used, involving 294 registered nurses grouped into three categories: Group I (non-CDSS, n = 98), Group II (simple rule-based CDSS, n = 96), and Group III (AI-assisted CDSS, n = 100). Eight-month data (February-September 2023) was gathered via structured observation checklists, validated measures of nursing practice, hospital records and patient satisfaction surveys. Data were analysed using one-way ANOVA with Bonferroni post hoc tests (p < 0.05). Results: AI-CDSS implementation produced marked improvements in clinical decision accuracy (84.7 ± 6.1% vs. 61.4 ± 8.2% in controls; p < 0.001), substantial reductions in medication error rates (2.1 ± 0.9 vs. 6.8 ± 1.9 per 100 orders; p < 0.001), shorter hospital stays (6.4 ± 1.7 vs. 9.8 ± 2.4 days; p < 0.001), and higher patient satisfaction scores (86.5 ± 6.9 vs. 63.2 ± 9.8; p < 0.001). The main challenges for implementation were the lack of digital infrastructure (74.5% for Group I) and AI-literacy training for nurses (81.6%). Conclusion: AI-powered CDSS resulted in improved nursing practice and patient outcomes in Iraqi hospitals. Continued infrastructure development and AI literacy training for nursing staff are vital for future use.