Sanjay Srinivas

Queue Cure

Regional outpatient clinics suffer from massive administrative overhead and high patient friction due to outdated, paper-based token slips and manual lobby shouting systems. This creates chaotic waiting environments, zero real-time data transparency for remote patients, and high rates of duplicate intake errors by receptionists. Furthermore, standard text-to-speech tools consistently mispronounce local Indian names, causing patient confusion and missed consultation slots. Process I engineered an event-driven architecture using Node.js, Express, and Socket.io to establish zero-latency cross-screen synchronization. I mapping out explicit multi-tenant data isolation logic in MongoDB via Mongoose to prevent cross-clinic leakage. For wait times, I initially tried a static ticking countdown, but it failed to capture real clinic velocity. I pivoted to an algorithmic rolling telemetry pipeline that continuously averages the last 5 completed sessions. To counter browser autoplay audio blocks, I implemented an explicit UI audio warm-up gate on the lobby terminal. Results Delivered a fully functional, real-time OPD management engine. Achieved 100% stable, zero-refresh live data updates across administrative panels, lobby monitors, and patient mobile hubs with a broadcast latency under 120ms. The rolling telemetry system successfully replaced hardcoded delay placeholders with realistic waiting windows, while the receptionist state toggle effectively eliminated duplicate entry mistakes during system-wide doctor breaks. Reflection If expanding the project, I would implement Redis adapter layers alongside Socket.io to ensure the real-time event distribution can scale horizontally across multiple backend server instances without state desynchronization. Additionally, I would add SMS token gateways using Twilio or WhatsApp Business APIs so patients could safely leave the clinic vicinity and receive automated queue warnings directly on their mobile networks.