Healthcare professionals are increasingly concerned about hospital-acquired infections (HAIs), as they can jeopardize patient safety and drive-up costs. In response, this academic project aimed to develop a system that tracks hospital-acquired infections and visualizes the data obtained to observe trends. The case–control methodology and SCRUM methodology were adopted in this study. A web-based application was developed that featured secure data capture, real-time alerting, and reporting capabilities. The data set was from an anonymous hospital containing 150,730 recorded cases over three years. The implemented system demonstrated several key successes. Out of 432 possible infections that can be acquired at a hospital, workers were able to specify the infections that they wanted to track. This system can detect early HAIs, assisting in faster treatment, and reducing infection severity.