<b>AI-DRIVEN DECISION SUPPORT SYSTEMS IN NURSING: TRANSFORMING CLINICAL JUDGMENT AND PATIENT CARE</b>

Abstract

Background: Artificial intelligence (AI) has become a change agent in healthcare and promises to change clinical decision-making opportunities. AI can be used in nursing to increase efficiency, minimize human error, and support evidence-based practice, among other things. Nevertheless, the attitudes, awareness, and desire of nurses to implement AI are still crucial prerequisites to effective integration into clinical processes. Purpose: This research targeted the awareness, perceived advantages, difficulties, and attitudes of nurses to AI as a decision-making tool and determined the reliability and validity of the tool applied. To add to that, the research has also investigated the effects of demographic characteristics like gender, education, and workplace on perceptions and readiness to embrace AI. Methods: A cross-sectional survey design was used, where 237 nurses in 9 hospitals, clinics, community care, and academic institutions were surveyed to gather data. The Likert scale questions (Q620) included in the structured type of questionnaire were demographic data. We used statistical analysis, which is the Shapiro-Wilk normality test, Cronbach's Alpha reliability, KMO, and Bartlett test of validity, independent sampling t-test, one-way ANOVA, Kruskal-Wallis test, Chi-square test, Pearson correlation, and regression analysis. Findings: The data were normally distributed (p > 0.05), and the reliability (Cronbach’s Alpha = 0.92) was excellent, as well as the validity (KMO = 0.82; Bartlett’s p = 0.001). Cross-group comparisons demonstrated that there was a high level of difference by gender, education, and workplace, and the chi-square analysis indicated that education and AI training were strongly correlated. Pearson correlation also revealed positive relationships between all items in the questionnaire, which showed that there was coherence between awareness, perceived benefits, and adoption. Regression analysis found awareness and understanding to have a strong positive influence on willingness to adopt AI, with age playing a positive but insignificant role. Conclusion: The research concludes that the willingness of nurses to embrace AI is majorly dependent on their awareness and knowledge of the technology, with the educational and workplace context facilitating the adoption of AI. It will be necessary to increase training opportunities and AI literacy among nurses to become effectively integrated into nursing decision-making. The ethical and policy implications of the AI implementation in the healthcare sector should be further studied in the future.

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