IMPACT OF ARTIFICIAL INTELLIGENCE ON CLINICAL DECISION SUPPORT SYSTEMS IN HOSPITAL SETTINGS

Abstract

BackgroundArtificial Intelligence (AI) in clinical decision support systems (CDSS) has become an essential tool in improving patient outcomes, enhancing diagnostic accuracy, and assisting in treatment planning. However, healthcare professionals’ perceptions and accessibility to AI-powered CDSS vary across different roles, impacting their effectiveness. Understanding how clinicians, physicians, and nurses interact with AI can provide valuable insights for improving AI integration in hospitals. ObjectiveTo evaluate the perception, accessibility, and practical use of AI-powered CDSS among clinicians, physicians, and nurses in a hospital setting, focusing on how these factors influence the overall adoption and effectiveness of AI. MethodsA cross-sectional survey was conducted in a hospital setting in Sheikhupura, Pakistan, over three months (Feb 2024 to Apr 2024). A total of 54 participants were divided into three groups: clinicians (n=18), physicians (n=18), and nurses (n=18). Data was collected using a structured questionnaire assessing perception (positive/negative), accessibility (easy/complex), and beneficiaries of AI (yes/no). Descriptive statistics, chi-square tests, and ANOVA were used for data analysis, performed using SPSS version 25. ResultsClinicians showed the highest positive perception of AI at 83.3% (15/18), compared to 77.8% (14/18) for physicians and 55.6% (10/18) for nurses. AI accessibility was reported as easy by 66.7% (12/18) of clinicians, 55.6% (10/18) of physicians, and 44.4% (8/18) of nurses. Beneficiaries of AI were 72.2% (13/18) of clinicians, 66.7% (12/18) of physicians, and 50% (9/18) of nurses. Statistically significant differences were observed among the groups (p < 0.05). ConclusionThe study demonstrated that while clinicians and physicians generally have a positive perception and easier access to AI, nurses experience more challenges in both areas. Targeted interventions, including training and support, are essential to improving AI accessibility and perception across all healthcare professional groups for optimal clinical decision-making.

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