Healthcare-associated infections (HAIs) are infections that patients acquire during the course of receiving treatment for other conditions within a healthcare setting. HAI is the most common complication or comorbidity of hospitalized patients, and is becoming major worldwide causes of death and disability. Also, there are associated financial costs substantial to both patients and healthcare systems. HAIs are critical patient safety and healthcare quality issues. Prevention and reduction of such infection has become one of the top priorities for health care. We focused on healthcare-associated urinary tract infection (HAUTI), which is the most common type of HAI. We proposed an approach to build a detection model for HAI surveillance based on the variables extracted from the electronic medical records (EMRs). Moreover, we developed an integrated HAI surveillance information system (called iHAUTISIS) based on existing EMR systems of the hospital for improving the work efficiency of infection control professionals (ICPs). Therefore, the system can further facilitate the HAI surveillance and reduce ICPs? surveillance workload.