This study presents a robust and explainable AI framework for analyzing complex EMR data to identify key risk factors and predict CPE-related outcomes. Our findings underscore the superior performance of the Transformer models and highlight the importance of diverse clinical and network features. The transparent interpretability offered by our XAI approach provides actionable insights for infection prevention and control, paving the way for more targeted interventions and ultimately enhancing patient safety within acute healthcare settings.