Loshmi

Queue Cure

Many clinics in India still rely on paper token slips and manual queue management. Patients often wait for long hours without knowing when their turn will come, while receptionists manage queues manually. This creates confusion, delays, and an inefficient patient experience. Queue Cure aims to digitize the clinic queue system by providing real-time token tracking and estimated waiting times. Process Analyzed the problem and identified the key challenges in clinic queue management. Designed the user interface for Receptionist Dashboard and Patient Waiting Room. Developed a real-time queue management system. Implemented token generation and patient queue tracking. Added estimated waiting time calculation based on consultation duration. Created a Socket.IO-based synchronization workflow for instant updates. Prepared GitHub repository, README, and project documentation. Results Successfully transformed a manual clinic queue process into a digital real-time management system. Enabled instant synchronization between receptionist and patient displays using Socket.IO. Improved patient experience by providing visibility into queue status and estimated waiting times. Reduced confusion and dependency on manual token announcements. Created a user-friendly interface that can be easily adopted by small and medium-sized clinics. Demonstrated the practical application of real-time web technologies in healthcare operations. Improved operational efficiency by automating token gene Reflection ntegrate a cloud database to store patient and appointment history permanently. Implement secure authentication and role-based access for clinic staff. Add SMS, WhatsApp, and email notifications for patients when their turn approaches. Introduce appointment booking and pre-registration features. Add support for multiple doctors and consultation rooms. Build a comprehensive analytics dashboard to monitor patient flow and clinic performance. Implement multilingual support to improve accessibility for diverse users. Conduct real-world testing with clinics and collect user feedback for iterative