Secure Online Patient Appointment Booking and Encrypted Medical History Management

Abstract

The rapid digital transformation of healthcare services has created a strong demand for secure, efficient, and user-friendly systems to manage patient appointments and sensitive medical information. Historically, healthcare institutions relied on manual registers and isolated digital tools for appointment scheduling and record maintenance, which often resulted in inefficiencies, data inconsistency, and limited accessibility. The problem is further intensified by the increasing volume of patients, the need for timely medical services, and strict requirements for data confidentiality. Traditional systems lack centralized control, real-time updates, strong authentication mechanisms, and adequate protection for sensitive medical data, making them prone to errors, delays, and security vulnerabilities. These limitations highlight the need for a robust digital solution that can streamline scheduling workflows while ensuring secure handling of patient information. To address these challenges, this research proposes a secure online patient appointment booking and encrypted medical history management system built using a webbased architecture. This research integrates structured backend processing with Flask, secure data persistence using SQL Alchemy (SQLA), Object Relational Mapper (ORM), and encrypted user authentication through bcrypt hashing (BCH). Role-based access control (RBAC) ensures that patients and administrators access only authorized functionalities, while automated workflows reduce manual intervention and scheduling conflicts. The system also provides dynamic dashboards for improved visibility and decision-making. The significance of this research lies in its ability to enhance operational efficiency, improve data security, and support scalable healthcare service delivery. By combining secure authentication, structured data management, and intuitive user interaction, the system demonstrates a reliable and performance-optimized approach suitable for modern healthcare environments. The proposed solution not only overcomes the limitations of traditional appointment systems but also establishes a strong foundation for future digital healthcare applications.