Healthcare-Associated Infections (HAI) are important quality indicators of healthcare, a leading cause of mortality and morbidity worldwide, and contributors to lower medical quality and increases in medical costs. Based on the definition and determining criteria of healthcare-related infections stipulated by Taiwan’s Centers for Disease Control, Department of Health, we created a program for an HAI determining rule, as well as an HAI monitoring system environment. With a data warehouse and data mining techniques as the core, we integrated all HAI-related data as analytical information for the purpose of decision-making. Key decision information was presented visually in a dashboard. In this way, infection control professionals are able to peruse abundant HAI information through a visual interface at anytime, anywhere. Traditionally, operation is done manually through continuous monitoring and automatic surveillance management. Decision makers can assess measuring indicators in real-time, which is critical to the management of HAI. This also allows HAI control professionals to cross-analyze and understand potential infection trends, and assist hospitals in developing a suitable HAI monitoring mechanism. By using the developed system, we can discover healthcare-related infection abnormalities earlier and provide infection control professionals with the ability to check on and conduct pre-decision analyses.