Queue Cure '26

76% of India's 1.5 million clinics still run on paper token slips and shouting. Patients wait 2–3 hours with zero visibility into when they'll be called. Doctors have no dashboard. Receptionists manage everything from memory. Process We started by identifying the main problem in clinics: patients have no visibility into queue status and receptionists manually manage tokens. We designed a simple two-screen system—one for receptionists and one for patients. React was chosen for the frontend, Node.js and Express for the backend, MongoDB for data storage, and Socket.IO for real-time synchronization. Initially, we considered periodic polling for updates, but it introduced delays and unnecessary requests. We switched to Socket.IO for instant updates across screens. We implemented dynamic wait-time calculation based on average consultation time and queue length. Edge cases such as empty queues, skipped patients, duplicate entries, and simultaneous actions were also considered and handled. Results Successfully built a real-time queue management system where both screens update instantly without refresh. Wait times are calculated dynamically using actual queue data and consultation duration. The solution reduces uncertainty for patients and minimizes manual workload for receptionists. Testing confirmed accurate token progression, real-time synchronization, and reliable wait-time estimation. Future improvements could include SMS notifications, multi-doctor support, and appointment booking integration. Reflection Given more time, I would implement role-based authentication, support multiple doctors and departments, add WhatsApp/SMS notifications, and introduce analytics dashboards for clinics. I would also conduct user testing with clinic staff and patients to gather feedback and further improve usability and efficiency.