Modern healthcare systems generate large volumes of heterogeneous data, including real-time sensor readings, structured electronic health records (EHRs), unstructured clinical notes, and diagnostic imaging. Ensuring the secure, high-quality, and interoperable integration of such multimodal data remains a major challenge. This paper introduces a modular healthcare data management framework that integrates decentralized storage, permissioned blockchain, context-aware data quality assessment, and semantic enrichment of unstructured data. The architecture combines blockchain for decentralized management, immutable audit trail, and transparency of information which adds a degree of accountability to the system; IPFS for decentralized storage of sensitive files; BIGQA for real-time, context-sensitive data quality scoring; and biomedical NLP techniques for transforming narrative clinical notes into semantically meaningful insights. A proof-of-concept implementation simulates clinical use cases such as streaming heart rate data, lab test integration, and clinical text interpretation. Results show improved precision in risk alerts and high-quality scores, confirming the framework’s utility in supporting real-time, patient-centered healthcare workflows.
Chamoun et al. (Thu,) studied this question.
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