Queue Cure '26 – Real-Time Patient Queue Management System

While visiting clinics, I noticed that many hospitals still manage patients manually. Receptionists have to call patients one by one and patients keep asking how much time is left for their turn. This creates confusion, longer waiting times, and unnecessary crowding near the reception desk. I wanted to build a simple system where the receptionist can manage the queue easily and patients can see their live queue status, current token, patients ahead, and estimated waiting time in real time. Process I first understood the requirements and identified the two main users of the system: the receptionist and the patient. I designed two separate screens. The receptionist screen allows adding patients, generating tokens, setting consultation time, and calling the next patient. The patient screen displays the current token, number of patients ahead, and estimated waiting time. Initially, I considered refreshing the page after every update, but that would not provide a real-time experience. To solve this, I used Flask-SocketIO so that both screens update instantly whenever the receptionist performs an action. For data storage, I used SQLite because it is lightweight and easy to manage for a clinic queue system. I also added emergency priority support so urgent patients can be handled quickl Results The final system successfully provides real-time queue updates across both screens without requiring manual page refresh. Patients can view the current token, estimated waiting time, and queue progress instantly. Receptionists can manage the queue with fewer mistakes and faster operations. The solution also supports emergency patients and dynamic wait-time calculation based on the consultation time entered by the receptionist. Overall, the system makes the patient waiting experience more transparent and improves queue management efficiency. Reflection If I had more time, I would add SMS/WhatsApp notifications, doctor-wise multiple queues, appointment booking, and a cloud database so the system could be used across multiple clinics and hospitals.