Artificial Intelligence in Medical Care Automation Transforming Healthcare Delivery through Intelligent Systems
Artificial Intelligence (AI) is rapidly transforming healthcare delivery through automation of diagnostic, clinical, and administrative processes. Intelligent systems such as machine learning algorithms, decision support tools, and automated diagnostics are increasingly adopted to improve accuracy, efficiency, and patient-centered care. However, the effectiveness of AI in real-world clinical settings requires empirical validation. This study aimed to evaluate the impact of AI-based automation on clinical efficiency, diagnostic accuracy, patient satisfaction, system usability, and acceptance of AI among healthcare providers and patients. A quantitative, cross-sectional design was employed involving 240 participants (healthcare professionals and patients) from tertiary hospitals using AI technologies. Stratified random sampling ensured representation across departments. Two structured questionnaires (5-point Likert scale) were used. Data were coded and analyzed in SPSS 23 and STATA. Statistical tests included descriptive statistics, Cronbach’s alpha for reliability, Pearson’s correlation, and multiple linear regression to identify predictors of patient satisfaction and clinical efficiency. Descriptive analysis showed high ratings for clinical efficiency (M = 4.12), diagnostic accuracy (M = 3.95), and patient satisfaction (M = 4.03). Reliability coefficients were acceptable (α = 0.79–0.86). Correlation analysis revealed strong relationships among system usability, diagnostic accuracy, and satisfaction (r > 0.60, p < 0.01). Regression models confirmed system usability (β = 0.34) and diagnostic accuracy (β = 0.29) as significant predictors of patient satisfaction (R² = 0.54), and clinical efficiency (R² = 0.49). AI-based automation significantly enhances healthcare delivery when systems are user-friendly, accurate, and well-accepted. Future implementation should focus on optimizing usability and fostering trust among users.