Sobitha Babu

QUEUECARE

Most clinics in India still rely on paper token slips and manual queue handling, leading to long waiting times, poor visibility for patients, and increased workload for receptionists. Patients often wait for hours without knowing when they will be called, while clinic staff struggle to efficiently manage queues. Queue Cure '26 addresses this problem by providing a smart digital queue management system with real-time updates, intelligent wait time estimation, and improved communication between patients and clinics. Process I started by analyzing the challenges faced in traditional clinic queue systems and identified the need for a simple, user-friendly, and real-time solution. I designed separate interfaces for receptionists and patients, implemented queue management logic, and integrated live synchronization to ensure instant updates. Additional features such as analytics, multi-doctor support, alert notifications, and ML-based wait time prediction were incorporated to enhance patient experience and clinic efficiency. Results Queue Cure '26 successfully digitizes clinic queue management and provides real-time visibility to patients and staff. The system reduces manual effort, improves patient experience, minimizes confusion, and enables efficient handling of multiple doctors and queues. The solution also lays the foundation for future enhancements such as machine learning-based predictions, voice announcements, and automated notifications. Reflection Unlike conventional token systems, Queue Cure '26 focuses on delivering a complete patient experience rather than just managing queues. The system combines real-time synchronization, analytics, multi-doctor support, intelligent waiting time estimation, and future-ready ML capabilities. It is designed to be scalable, user-friendly, and adaptable for clinics of different sizes, making healthcare queue management smarter and more efficient.