SREEMATHI S S 25CS187

Queue Cure – Smart Patient Queue Management System

During visits to hospitals and clinics, patients often spend a long time waiting without knowing when their turn will come. Receptionists manage queues manually using registers or token slips, which makes it difficult to handle rush hours and sudden delays. Patients repeatedly approach the reception desk to ask about their status, creating confusion and increasing workload for hospital staff. We wanted to create a simple digital system that keeps track of the queue, displays the current token, and gives patients an estimate of their waiting time so that the waiting experience becomes less stre I started by observing how queues are usually managed in small clinics and diagnostic centres around us. The biggest issue I noticed was the lack of transparency in waiting times and the amount of manual work required from reception staff. Initially, I considered adding appointment booking and doctor scheduling features, but that made the system unnecessarily complex for a first version. I decided to focus on solving one problem well: managing walk-in patient queues efficiently. I designed separate views for receptionists and patients. Receptionists can add patients and call the next token, while patients can see the current token number, how many people are ahead of them, and an estimated waiting time. To make the estimate meaningful, we assumed an average consultation duration pe I tested Queue Cure using simulated patient arrivals and receptionist interactions to understand how the system would perform in a real clinic environment. The digital token system reduced the need for patients to repeatedly ask reception staff about their position in the queue and improved visibility into waiting times. During test scenarios involving approximately 50 patients, the system maintained queue order without manual intervention and reduced estimated waiting times from around 25-30 minutes to approximately 10-15 minutes through better organization and faster token handling. If I had more time, I would expand Queue Cure beyond basic token management by integrating features such as appointment scheduling, doctor availability tracking, and emergency patient prioritization. I would also improve waiting time predictions by using historical consultation data instead of relying on a fixed average consultation duration, making estimates more accurate during busy periods. Another improvement would be adding SMS or mobile notifications so patients can receive updates about their token status without needing to remain in the waiting area.