Akshara P
Featured project
Queue Cure '26
Many small and medium-sized clinics in India still rely on paper token slips and manual announcements to manage patient queues. Patients often wait 2–3 hours without knowing when they will be called, leading to frustration, repeated inquiries at the reception desk, and overcrowded waiting areas. Receptionists manually track patient order, estimate waiting times from memory, and announce token numbers, which increases workload and creates opportunities for errors. Patients have no visibility into queue progress, while clinics lack a simple digital solution that is affordable and easy to use. Process We began by analyzing the existing patient journey in clinics and identifying key pain points for both patients and receptionists. The primary issues identified were lack of queue visibility, manual token management, and uncertainty regarding waiting times. To validate the solution, we mapped the workflow of a typical clinic visit and designed two separate interfaces: a Receptionist Dashboard and a Patient Waiting Room Dashboard. We prioritized simplicity and real-time communication because most clinics require solutions that can be adopted without extensive training. Multiple interface layouts were considered before selecting a minimal dashboard design focused on speed and usability. We chose React for rapid frontend development, Node.js and Express for backend services, and Socket.io t Results Queue Cure successfully digitized the clinic queue management process and achieved real-time synchronization between receptionist and patient interfaces. The system provides instant queue updates, current token visibility, estimated waiting times, and live queue position tracking. The solution eliminates the need for paper-based token management and reduces uncertainty for patients by providing continuous visibility into queue progress. Receptionists can efficiently manage patient flow through a centralized dashboard, reducing manual effort and operational errors. The final prototype demonst Reflection Given more time, I would add database storage, WhatsApp/SMS notifications, and AI-based wait-time prediction. I would also conduct user testing with clinic staff to further improve usability and real-world adoption.