Modernizing Healthcare Master Data Management (MDM): Harnessing Real-Time Processing, IoT, and Blockchain - Banerjee, Somnath (International Journal of Computing and Engineering, 2025)
Purpose: This paper aims to propose a robust, future-ready master data management (MDM) architecture that addresses traditional MDM challenges by enhancing data accuracy, trust, and accessibility, while aligning with regulatory frameworks such as the 21st Century Cures Act and TEFCA. Methodology: Employing a qualitative design-oriented approach, the study combines literature review, technical architecture modeling, and real-world case analyses. Key interoperability standards (HL7/FHIR), decentralized identity protocols (DIDs), and smart contract frameworks were analyzed. The proposed architecture was validated through five empirical case studies, including Estonia’s blockchain-based national health system, and ICU telemetry streaming models. The architecture consists of four layers: IoT data ingestion, real-time stream processing (via Kafka and Flink), blockchain-based trust infrastructure, and a unified MDM layer. Findings: The architecture addresses longstanding MDM pain points: reducing integration latency from hours to seconds, eliminating duplication through blockchain-backed identity management, and enhancing auditability with immutable ledgers. Key benefits include real-time anomaly detection, improved chronic care monitoring, and secure multi-organizational data sharing. Clinical use cases demonstrated timely updates to patient records and improved data reliability across institutions. Comparative analysis highlighted the architecture’s ability to scale horizontally, support federated governance, and ensure compliance with both HIPAA and GDPR. Unique contribution to theory, practice, and policy: The study advances theoretical understanding of MDM in the context of decentralized and high-frequency healthcare environments. Practically, it offers a modular, interoperable solution for healthcare IT leaders seeking to modernize legacy infrastructures. From a policy perspective, it outlines a path toward data-sharing frameworks that balance innovation, compliance, and patient autonomy. This research establishes a blueprint for secure, scalable, and intelligent MDM, contributing to the ongoing digital transformation of healthcare systems globally.