Kaviya K

QueueCure – Real-Time Clinic Queue Management System

In many small and medium-sized clinics, patient queues are still managed using paper token slips and manual announcements. Patients often wait for long periods without knowing when they will be called, leading to frustration and overcrowded waiting areas. Receptionists must manually track the queue, which increases the chances of mistakes and delays. The objective of QueueCure was to build a simple real-time digital queue management system that provides transparency for patients and reduces the workload on receptionists. Process I first analyzed the problem and identified the two primary users: receptionists and patients. Based on the hackathon requirements, I designed two separate interfaces—a receptionist dashboard and a patient waiting room. The backend was developed using Node.js and Express.js to manage queue operations such as adding patients, calling the next token, and updating consultation times. Socket.IO was integrated to provide real-time communication between all connected screens without requiring page refreshes. The queue logic was implemented using an in-memory data structure. I created automatic token generation, wait-time calculation, and position tracking. To address concurrency issues, I implemented a locking mechanism using an isCallingNext flag to prevent multiple simultaneous Results The final solution successfully delivers real-time queue updates across both receptionist and patient dashboards without requiring page refreshes. Patients can instantly view the current token, their queue position, and estimated waiting time. Receptionists can manage the queue efficiently through a simple interface. The application meets all major hackathon requirements, including live synchronization, dynamic wait-time computation, and concurrency handling for queue operations. Reflection If given more time, I would integrate MongoDB to persist queue data across server restarts and implement user authentication for different roles such as receptionist and doctor. I would also add SMS or WhatsApp notifications to alert patients when their turn is approaching. Additional improvements would include a doctor dashboard, appointment booking support, queue analytics, and deployment to a cloud platform for production use.