Kartik Nair

Kartik Nair

Full-Stack Developer

Thadomal Shahani Engineering Collegeinternship, freelance
Open to roles
Problem SolvingGITSQLReact
Queue Cure '26

Queue Cure '26

Traditional clinics suffer from chaotic waiting rooms and severe receptionist burnout. We identified a critical architectural gap: existing queue systems rely on manual browser refreshes, creating a latency disconnect between the doctor's dashboard and the patient waiting screen. Furthermore, legacy systems use hardcoded wait-time estimates (e.g., a static 15-minutes per patient), resulting in highly inaccurate forecasts. This leads to massive cognitive overload for receptionists managing 50+ patients daily, and intense anxiety for patients who lack real-time visibility into their status. I mapped the asynchronous flow between Receptionists, Doctors, and Patients. Initially, I tried HTTP REST polling to sync screens. This failed, causing UI flickering and high latency. I pivoted to a WebSocket architecture (Socket.io). This enabled the Express backend to push events instantly to React, achieving zero-latency synchronization without page refreshes. To fix inaccurate wait times, I abandoned static math. I built an algorithm that computes a dynamic rolling average using live timestamp differences between 'Called' and 'Completed' states. Finally, I hardened the receptionist portal with strict dual-layer input validations to prevent human errors. The implementation yielded a 100% reduction in manual page refreshes across all clinic screens. The WebSocket integration achieved near 0-ms synchronization latency between the Doctor's dashboard and the Patient Waiting Room. The dynamic wait-time algorithm completely eliminated the 15-minute static hardcoding, providing patients with highly accurate estimates based on live session averages. Furthermore, the strict dual-layer form validations (React/Express) drove receptionist input errors down to zero, significantly speeding up the patient onboarding workflow. While the real-time sync is flawless, the infrastructure currently relies on a free-tier Render backend. This causes a 60-second "cold start" delay if the server goes to sleep. Next time, I would implement a CRON keep-alive script to ensure instant initial loads. Additionally, I would integrate a Service Worker with IndexedDB to create an "offline-first" queue. This would allow receptionists to seamlessly register patients even during internet outages, securely queuing the API requests to automatically sync with MongoDB once the connection is restored.

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