<![CDATA[Tuberculosis (TB) remains a significant public health challenge in Indonesia, including at Hospital X Bandung, where the diagnosis process still relies on paper-based clinical pathways that are prone to errors and inefficiencies. This research aims to design a web-based information system to digitize the clinical pathway of TB diagnosis to improve the accuracy, consistency, and speed of patient treatment. The system development method uses the Waterfall approach with the stages of needs analysis, design, implementation, and testing. The system was developed using the Flask framework with the Python programming language, utilizing SQLAlchemy for SQLite database management. The implementation results include key features such as patient data input, structured clinical pathway forms, medical record management, and treatment evaluation tracking. Black box testing shows that all system functionality is running as expected, including data validation and patient information storage. This system is expected to reduce the variation in clinical practice, improve medical documentation, and facilitate real-time patient monitoring. Future development suggestions include integration with other hospital systems, the addition of artificial intelligence-based prediction features, and optimization of the interface for mobile access.]]>
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