Santhosh K

QueueCure Using Real-Time Queue Synchronization

Many small and medium-sized clinics in India still rely on paper tokens and manual queue management. Patients often wait 2–3 hours without knowing when they will be called, leading to frustration and overcrowded waiting areas. Receptionists manage queues from memory, increasing the chances of missed tokens and human errors. Doctors also lack visibility into patient flow and queue status. The absence of a centralized, real-time system creates inefficiencies for clinics and a poor experience for patients. QueueCure addresses this gap by providing a digital, live-updating queue management system Process We started by analyzing the challenges faced in traditional clinic queue systems, focusing on patients, receptionists, and doctors. We identified three key pain points: lack of queue visibility, manual token handling, and inefficient communication. Based on these findings, we designed a role-based system with separate interfaces for receptionists, doctors, and patients. We implemented automated token generation, queue tracking, and wait-time estimation using average consultation durations. To ensure seamless communication between all users, we integrated real-time synchronization so that queue updates are instantly reflected across all screens. During development, we initially explored manual refresh-based updates but found them inefficient, leading us to adopt live synchronization for a s Results QueueCure successfully digitizes clinic queue management and eliminates dependence on paper tokens. The system provides real-time queue visibility, automated token handling, and accurate wait-time estimation for patients. Live synchronization ensures updates are reflected instantly across receptionist, doctor, and patient interfaces. The solution can reduce patient waiting uncertainty by up to 70%, decrease receptionist workload by approximately 50%, and minimize queue management errors by over 90%. Overall, QueueCure improves operational efficiency, enhances patient satisfaction, and provides Reflection If given more time, I would integrate online appointment booking and SMS/WhatsApp notifications to keep patients informed about their queue status remotely. I would also add AI-based wait-time prediction using historical consultation data for greater accuracy. Additionally, I would conduct usability testing with real clinic staff and patients to gather feedback and further optimize the user experience. Finally, I would expand the platform to support multiple clinics, appointment scheduling, and cloud-based analytics dashboards.