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WaitWise – Smart Hospital Queue Management System

Reduced patient waiting confusion by providing live queue status, emergency prioritization, and real-time wait estimation.

ramya ananthasivaram

Overview

Hospitals and clinics often face long patient queues with poor visibility into waiting times. Patients are uncertain about when their turn will come, while receptionists manually manage queues without a proper system. Emergency cases also need faster prioritization, but traditional token systems cannot dynamically reorder patients. This creates confusion, delays, and poor patient experience. WaitWise solves this by introducing a live queue management system with real-time patient tracking, emergency prioritization, and estimated waiting times. I started by identifying the common problems in hospital waiting areas such as unclear token progress, no live updates, and no priority handling for emergency patients. I designed a simple two-panel system: one for the receptionist to manage the queue and another for patients to track live status. The backend was built using Spring Boot and MySQL for storing queue data, while the frontend used HTML, CSS, and JavaScript for live interaction. I implemented features step-by-step including patient addition, calling next patient, cancellation, emergency priority logic, and average wait time calculation. Finally, I improved UI/UX for better readability and professional appearance. WaitWise successfully provides real-time queue visibility for patients and staff. The receptionist can efficiently manage patient flow, call the next patient, and prioritize emergencies instantly. Patients can see the current patient, next patient, queue ahead, and estimated waiting time live without asking staff repeatedly. This improves transparency, reduces confusion, and optimizes hospital workflow. In the future, I would enhance WaitWise by adding WebSocket-based live synchronization instead of polling for faster real-time updates. I would also integrate SMS notifications, doctor availability tracking, and patient appointment scheduling to make the system more scalable and production-ready.

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