Empowering Health Information System Education and Practice with Bahmni: Open-Source Digital Health and Medical Informatics Innovation
Bahmni is an innovative open-source hospital management system designed to address the challenges of low-resource healthcare settings. By integrating electronic medical records (OpenMRS), billing and inventory management (Odoo), laboratory information systems (OpenELIS), and medical imaging (PACS), it provides a comprehensive digital health solution. Its intuitive interface, offline functionality, workflow flexibility, and modular architecture make it particularly valuable for both clinical implementation and medical education.This study explores Bahmni’s dual role as a healthcare management platform and an educational tool for training future medical professionals. We successfully deployed Bahmni in an academic setting by implementing it on Windows-based systems using Docker containerization—a significant technical achievement given its native Linux environment. This adaptation enabled hands-on student training across multiple clinical departments, including radiology, laboratory sciences, and respiratory care, bridging the gap between theoretical instruction and real-world hospital practice.Our findings demonstrate that Bahmni effectively enhances health informatics education by providing students with practical experience in managing electronic health records, navigating clinical workflows, and processing diagnostic tests. The system’s ability to function efficiently in non-Linux environments significantly expands its applicability in academic institutions with limited IT infrastructure. Additionally, student feedback highlighted improved competency in digital health management, confirming Bahmni’s value as a teaching tool.This paper details Bahmni’s system architecture, implementation strategy, and educational outcomes, emphasizing its scalability and adaptability. The results underscore the transformative potential of open-source solutions like Bahmni in advancing medical education, particularly in resource-constrained settings.
Authors
- Atef Raslan
- abeer eldessouki
- Jihan Farouq
- Nourhan Abdeltwab
Institutions
- Misr University for Science and Technology (EG)
Publication Details
- Journal
- Advanced Sciences and Technology Journal.
- Published
- 2025-08-22
- DOI
- https://doi.org/10.21608/astj.2025.391519.1067
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00