Queue Cure '26 – Real-Time Smart Clinic Queue Management System

Queue Cure addresses the lack of transparency in traditional clinic waiting rooms, where patients often face anxiety due to unpredictable wait times. Manual tracking leads to overcrowding and frequent interruptions for receptionists, creating a stressful environment for both staff and visitors. I identified a gap where real-time data could be used to provide live updates and accurate, data-driven estimates. By digitizing this flow, I aimed to reduce perceived wait times and improve operational efficiency in high-pressure healthcare settings. Process I chose a real-time-first architecture using Node.js and Socket.io to ensure that the patient view updates the millisecond a receptionist clicks "Call Next." I implemented a glassmorphism-based UI design to create a premium, "calming" aesthetic that contrasts with the typical sterile feel of medical software. To handle concurrency, I centralized all queue mutation logic on the server to prevent race conditions during simultaneous patient entries. I iterated on the wait-time logic, moving from a static input to a dynamic calculation based on actual consultation durations. Finally, I focused on making the receptionist view "mistake-proof" with clear, accessible controls for rapid action. Results The working prototype successfully delivers zero-refresh updates across both views, achieving a latency of under 50ms for live synchronization. Testing showed that the data-driven wait estimates provided a clear, predictable timeline, reducing the need for manual status queries at the reception desk. The "Call Next" efficiency was improved by consolidating all primary actions into a one-click dashboard interface. For future iterations, I’d focus on integrating a notification system to alert patients via SMS when their turn is approaching. These results demonstrate a robust, scalable foundation Reflection I would integrate a persistent database like PostgreSQL for historical analytics on doctor efficiency and peak hours. Adding multi-department support would allow one receptionist to manage several doctors simultaneously. A QR-code check-in system could streamline registration and eliminate manual entry errors. Furthermore, I’d add SMS notifications to let patients wait flexibly outside the clinic. Finally, I’d implement role-based authentication to secure the receptionist controls. This would evolve the prototype into a fully production-ready healthcare management platform.