Abstract: Efficient management of doctor appointments and patient interactions is a major challenge in healthcare systems, particularly in institutes relying on traditional coordination and record-keeping. Conventional hospital administration methods are error-prone, time-consuming, and without real-time communication between doctors and patients. This paper illustrates the concept and design of a web-based Doctor Panel Management System using the MERN stack, with a list of features such as automation of appointment scheduling, payment processing, and communication through an integrated AI chatbot. It includes a responsive admin panel designed with React and Tailwind CSS, using the Context API for optimized state management. A RESTful API layer using Node.js/Express will securely interact with MongoDB, while the Razorpay integration offers a reliable and seamless digital payment mechanism. The AI chatbot enhances patient engagement with automation for appointment status tracking and queries. Experimental results show a reduction in manual effort by 40% and increased reliability within appointment scheduling. This research focuses on the potential of full-stack automation combined with AI in increasing accessibility to healthcare and operational efficiency. Future work may look into integrating predictive analytics and voice-based AI assistants for advanced healthcare automation.
Keywords: Doctor Panel System, MERN Stack, Healthcare Automation, AI Chatbot, Razorpay, RESTful API, Context API
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DOI:
10.17148/IJARCCE.2025.1412138
[1] Varada Alekhya, Abdul Musawwir, Akash G, Amith Kumar M and B V N Shanmukha, "DOCFLOW – AI POWERED HEALTH CHECK IN PLATFORM SYSTEM," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.1412138