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Impact of Artificial Intelligence on Clinical Decision-making and Support Systems in Hospital Environments

Year: 2025

Type: article

Abstract: Background: The growing complexity of clinical practice and demand for high-quality care have amplified the need for advanced decision-making tools in hospitals. Artificial Intelligence (AI) has emerged as a transformative force in enhancing Clinical Decision Support Systems (CDSS), with the potential to improve accuracy, efficiency, and outcomes in healthcare delivery. Objective: To assess the impact of integrating AI into CDSS on clinical decision-making quality, workflow efficiency, patient outcomes, and clinician satisfaction in tertiary hospital settings. Methods: This quasi-experimental study was conducted over eight months in two tertiary care hospitals in Lahore. A total of 150 clinicians were divided equally into pre- and post-implementation groups. Data collection tools included the Clinical Decision Quality Score (CDQS), time-motion analysis for workflow efficiency, hospital records for patient outcomes, and the modified Technology Acceptance Model (TAM) for clinician satisfaction. Statistical analysis included paired t-tests, chi-square tests, and repeated measures ANOVA to evaluate normally distributed data. Results: Post-implementation of AI-CDSS, the mean CDQS significantly improved from 78.4 to 86.9 (p < 0.001). Decision time per patient and turnaround time reduced notably (p < 0.001), while actioned alerts increased from 63% to 82% (p < 0.01). Patient outcomes also improved, with reductions in 30-day readmission rates (16.4% to 11.1%), average hospital stay (5.7 to 4.9 days), and adverse events (11.8% to 7.3%). Clinician satisfaction scores showed significant enhancement across all TAM dimensions (p < 0.001). Conclusion: AI integration into CDSS demonstrably improved decision accuracy, clinical workflow, patient safety, and provider satisfaction, advocating its broader implementation in hospital settings.

Source: Insights-Journal of Health and Rehabilitation

DOI: 10.71000/zhqww010

Authors: Edward Edison, Aqib Dil Awaiz, Sania Sehr, Asna Afzal, Hafsa Tahir, Maida Aslam, Muhammad Waleed Khan

Institutions: University of Management and Technology, Minhaj University Lahore, National University of Sciences and Technology

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

OpenAlex ID: W4411378479

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