The Problem
Patients, doctors, and administrators were using disconnected systems for health records, vital tracking, appointments, prescriptions, messaging, and notifications. Doctors also had to manually review patient data, making it difficult to identify serious health risks quickly.
What We Built
We built a MERN-based healthcare platform with separate experiences for patients, doctors, and administrators. The frontend uses React with role-based routing for dashboards, vital tracking, health trends, appointments, prescriptions, messaging, notifications, and blog content. The backend uses Node.js and Express with a layered architecture of routes, controllers, services, models, and middleware. MongoDB with Mongoose manages users, patient profiles, doctor profiles, vital records, appointments, prescriptions, blogs, conversations, messages, notifications, and audit logs. Authentication uses JWT access tokens, rotating refresh tokens, and bcrypt password hashing. Socket.io provides private real-time messaging and notification delivery. We also fine-tuned and integrated an AI model into the backend. The model continuously evaluates patient data against clinically informed thresholds and risk patterns. When a potential critical condition is detected, the system creates a red-flag alert for the appropriate doctor. The AI works as a clinical decision-support tool. It helps doctors prioritize risk and review patient information, but it does not replace medical judgment or independently diagnose or prescribe treatment.
Result
The platform brings patient monitoring, doctor communication, appointments, prescriptions, messaging, notifications, and health-risk alerts into one system. Doctors receive faster visibility into potential red-flag situations, while patients receive continuous monitoring support and a clearer way to communicate with their care team. The system is designed to improve response time, reduce manual monitoring work, and support safer healthcare workflows.
