Srikishan.S

Transforming Patient Waiting into Predictable Care

Most small and medium-sized clinics in India still rely on paper tokens and manual queue management. Patients often wait 2–3 hours without knowing their position in the queue or estimated waiting time, leading to frustration and overcrowding. Receptionists manually track patient order, increasing the chances of errors, missed tokens, and inefficient workflow. There is a lack of a simple, affordable, and real-time solution that provides visibility to both patients and clinic staff. it addresses this gap by digitizing clinic queue operations through live synchronization. I started by analyzing the workflow of a typical clinic reception desk and identifying the major pain points faced by patients and staff. The primary requirements were real-time queue updates, visibility of the currently served patient, and wait-time estimation without requiring page refreshes. I designed the system with two separate interfaces: a Receptionist Dashboard for queue management and a Patient Display Screen for live queue tracking. To ensure instant updates across both screens, I implemented Socket.IO for bidirectional real-time communication between the frontend and backend. The backend was developed using Node.js, Express.js, and MongoDB to manage patient records and queue states. The frontend was built using React, focusing on simplicity and quick interaction for reception It successfully transforms traditional paper-based clinic queues into a transparent digital experience. The system enables real-time synchronization between receptionist and patient displays without requiring manual refreshes. Patients can view their queue position, current token being served, and estimated waiting time, while receptionists can efficiently manage patient flow through a centralized dashboard. Unlike traditional queue systems that only display token numbers, It focuses on transparency and real-time visibility. I implemented a dual-screen architecture where both the receptionist dashboard and patient display remain synchronized instantly using Socket.IO without requiring page refreshes. Instead of hardcoded waiting times, the system dynamically estimates wait times based on queue length and consultation duration. I also designed the interface to be simple for receptionists while providing patients with clear information about the current token, tokens ahead, and expected