AI-Driven Healthcare Management Platform: Enhancing Accessibility, Efficiency, and Security in Digital Health Systems

Abstract

The Healthcare Management Platform is a web-based E-Health Center developed using the MERN stack (MongoDB, Express.js, React.js, Node.js) to enhance healthcare accessibility and efficiency. This study presents a quantitative analysis of the system’s performance based on user engagement metrics, appointment booking success rates, chatbot response accuracy, and system load handling capacity. The platform streamlines patient-doctor interactions by providing an intuitive appointment scheduling system, a chatbot for symptom analysis, and a role-based dashboard for doctors, patients, and administrators. In a pilot usability test involving 200 users, the system recorded a 73% reduction in appointment scheduling time compared to traditional phone-based systems. The chatbot achieved an 87% accuracy rate in symptom-based recommendations when validated against medical databases. Additionally, server response times averaged 320ms under a simulated load of 5,000 concurrent users, demonstrating the platform’s scalability. The study also found a 42% increase in patient engagement, measured through repeated platform usage and interactions per session. Security audits confirmed 99.8% protection against common cyber threats, ensuring data confidentiality. Furthermore, 91% of surveyed users reported a positive user experience, citing ease of use, clarity of information, and reduced waiting times. These results highlight the platform’s potential in bridging healthcare accessibility gaps and improving efficiency through digital transformation. Future work will focus on AI-driven diagnostics, telemedicine integration, and blockchain-based patient data security to further enhance the platform’s capabilities. The findings underscore the significance of technology-driven healthcare solutions in improving patient outcomes and operational efficiency in modern healthcare ecosystems.