SwiftQueue

In most neighbourhood clinics, a patient walks in, gets a paper slip, and sits — with no idea how long the wait is. Receptionists manage everything from memory. Doctors have no dashboard. The result: 2–3 hour waits, missed tokens, and frustrated patients who leave before being seen. Process Queue Cure solves the real issue in clinics—not paper tokens, but the lack of queue visibility. Patients often wait without knowing how long it will take, creating anxiety and constant interruptions for receptionists. Using Django, SQLite, and Socket.IO, the system provides real-time queue updates across phones, reception desks, and waiting room displays. Wait times are calculated dynamically based on the number of patients and consultation duration. With instant updates, automatic token management, and reliable handling of edge cases, Queue Cure transforms clinic waiting into a transparent, stress-free experience. Results results and outcome in 400 charcateeer 3:19 PM Replaced paper token slips with a live digital queue visible on every patient's phone and the waiting room screen. Receptionists add patients and issue tokens in under 10 seconds. Wait time is computed from real data — patient count times average consultation time — and updates the moment anything changes. Both screens stay in sync via Socket.IO with zero page refreshes. Edge cases like empty queues, duplicate calls, and daily resets are all handled gracefully. A neighbourhood clinic can go from paper chaos to a fully live queue in one command. Reflection I'd swap SQLite for PostgreSQL with `select_for_update()` to handle concurrent receptionists safely at scale. I'd add SMS notifications so patients don't need to watch the screen. I'd build a doctor's dashboard showing average consultation time trends. I'd also add a patient self-check-in QR code at the clinic entrance — cutting receptionist workload entirely for walk-ins.