Queue Cure – Real-Time Clinic Queue Management System

Many clinics still rely on manual token systems where receptionists manage patient queues verbally or on paper. Patients often wait for long periods without knowing when their turn will arrive, leading to confusion and frustration. Receptionists must continuously answer queue-related questions while managing patient records. The lack of real-time visibility creates inefficiencies for both patients and clinic staff. Queue Cure addresses this problem by providing a real-time digital queue management system that keeps receptionists and patients synchronized through live updates. Process I started by analyzing how clinic queues are usually managed and identified two main users: receptionists and patients. The primary goal was to keep both views synchronized in real time without page refreshes. I built a Receptionist Dashboard to add patients and call the next token, and a Patient Waiting Room to display the current token, queue position, and estimated wait time. Socket.IO was used for instant communication between clients and the server. The backend was developed using Node.js, Express, and Socket.IO, while React was used for the frontend. Queue data is stored in a JSON file for persistence. I tested scenarios such as empty queues, multiple connected users, page refreshes, and continuous patient additions to ensure reliable performance. Results The final solution successfully provides real-time queue updates across all connected clients without requiring page refreshes. Patients can view the currently serving token, estimate their waiting time, and track queue progress transparently. The system supports live synchronization using Socket.IO, automatic token management, queue persistence, and status tracking for waiting, serving, and completed patients. Testing confirmed that updates are reflected instantly across multiple browser windows and devices. Reflection If given more time, I would allow receptionists to configure average consultation time dynamically instead of using a fixed value. I would also add SMS or WhatsApp notifications, authentication, multi-doctor support, and database integration for better scalability. Additional analytics such as average waiting time and daily patient statistics would further improve the system.