Transforming Unstructured Medical Data: A Digital System for Anonymized Electronic Health Records

The exponential growth of medical data presents significant challenges in the handling, processing, and secure storage of patient records. This paper introduces an advanced digital system designed to extract and store anonymized patient medical records within a national cancer research network. Utilizing modern web technologies and advanced Natural Language Processing techniques, the proposed solution effectively manages the complexities of unstructured and semi-structured data formats. The system, featuring a user-friendly web application, enhances data processing and accessibility. Validated through the successful extraction and structuring of data from over 40 patient records, it demonstrates significant potential in clinical research by reducing manual workload and improving data management. This paper details the system's architecture, functionalities, and benefits, emphasizing its impact on modernizing healthcare data management and its future applicability in the broader healthcare industry.