Queue Cure – Smart Healthcare Queue Management System

Many clinics still rely on manual token systems where patients have no visibility into queue status or expected waiting time. Receptionists manage patient flow manually, doctors lack a centralized consultation dashboard, and emergency patients are often not prioritized effectively. This leads to long waiting times, poor patient experience, communication gaps, and inefficient clinic operations. The challenge was to build a real-time queue management system that improves transparency, prioritizes emergency cases, and synchronizes information across reception, doctor, and patient display screens. Process I analyzed the workflow of outpatient clinics and identified three key users: Receptionist, Doctor, and Patient. To address manual queue management issues, we developed a full-stack healthcare queue management system using Flask, MongoDB, JavaScript, HTML, CSS, and Socket.IO. The solution includes: • Reception Dashboard for patient registration and queue control. • Doctor Dashboard for consultation tracking and notes. • Patient Display Board for real-time queue visibility. We further enhanced the system with emergency patient prioritization, analytics, returning patient detection, report export, and real-time synchronization across all dashboards. Results The final system successfully provides real-time queue visibility across all connected dashboards. Emergency patients are automatically prioritized, consultation progress is tracked, doctor notes are stored, and administrators can monitor clinic performance through analytics. The platform includes live synchronization, patient history tracking, emergency alerts, exportable reports, and cloud deployment. These features significantly improve transparency, operational efficiency, and patient experience compared to traditional manual queue systems. Reflection Given additional time, I would extend the system with AI-based waiting time prediction, QR-based patient check-in, multi-doctor scheduling, appointment booking, mobile notifications, and predictive analytics. I would also enhance security with role-based access control and optimize the architecture for large-scale hospital deployments.