A Web-Based Blood Bank Management System for Efficient Donor– Recipient Matching and Inventory Optimization

Abstract

The availability of safe and adequate blood supply is a critical component of modern healthcare systems. Blood banks play a vital role in collecting, storing, and distributing blood to patients in need. However, traditional blood bank management systems often rely on manual processes, leading to inefficiencies, delays, and errors in donor–recipient matching and inventory management. This research presents a web-based Blood Bank Management System designed to improve operational efficiency, ensure real-time availability tracking, and facilitate effective communication between donors, recipients, and administrators. The proposed system is developed using Python and the Django web framework, providing a scalable and secure platform for managing blood bank operations. It enables users to register as donors, search for available blood types, and request blood units during emergencies. The system maintains a centralized database that stores donor information, blood inventory, and transaction records.The system incorporates features such as real-time inventory updates, donor eligibility tracking, and automated notifications. These functionalities ensure that blood availability information is always up-to-date and accessible. The system also supports role-based access control, allowing administrators to manage data securely while providing limited access to users.Data validation and error handling mechanisms are implemented to ensure data integrity and system reliability. The web-based architecture allows users to access the system from any location, improving accessibility and response time during emergencies. The proposed system addresses the limitations of traditional blood bank management approaches by automating key processes and reducing human intervention. It enhances transparency, reduces operational costs, and improves service quality.Experimental evaluation demonstrates that the system effectively manages blood inventory and reduces response time in emergency situations. The integration of modern web technologies ensures scalability and ease of maintenance.This research contributes to healthcare informatics by providing a practical and efficient solution for blood bank management. Future work may involve integrating machine learning techniques for demand prediction and incorporating mobile applications to further enhance accessibility.