Queue Cure – Real-Time Clinic Queue Management System

Many small and medium-sized clinics in India still rely on paper tokens and manual queue management. Patients often wait for long periods without knowing when they will be called, leading to frustration and overcrowded waiting areas. Receptionists are responsible for managing the entire queue manually, making it difficult to track patient status and estimated waiting times.Queue Cure was built to digitize this process by providing a centralized queue management system that offers visibility to both receptionists and patients. The goal was to reduce uncertainty, improve clinic operations, and I started by breaking down the problem into three core workflows: patient registration, queue progression, and patient visibility. The first step was designing a simple token-based queue system where every patient receives a unique token upon registration. The backend was implemented using Spring Boot and Spring Data JPA, with H2 Database used for rapid development and testing. I created REST APIs for adding patients, advancing the queue, and retrieving queue status. To maintain queue consistency, patient states were managed using three statuses: WAITING, IN_PROGRESS, and COMPLETED.Once the backend APIs were functional, I built two separate React dashboards. The Receptionist Dashboard allows staff to add patients, call the next patient, and monitor the queue. The Patient Waiting Room Da The final solution successfully digitizes clinic queue management through a full-stack web application. Receptionists can register patients, manage token progression, and monitor queue status through a dedicated dashboard. Patients receive real-time visibility into the currently served token, their position in the queue, and estimated waiting times.The project demonstrates end-to-end full-stack development skills including frontend development with React, backend API development using Spring Boot, database integration with JPA, and state management for real-world workflows. The architecture If given more time, I would replace polling with WebSockets to achieve true real-time updates across dashboards. I would also introduce appointment scheduling, multi-doctor queue support, analytics dashboards, and AI-based wait-time prediction. Additionally, I would deploy the application to the cloud and integrate authentication for clinic staff and patients.Also i would further plan to integrate angentic ai to handle the scheduling the appointments in future .