Healthcare Big Data Management: A Taxonomy of Data Management Systems and the Emerging Role of Blockchain

Abstract

Technological advancements in healthcare have led to the generation of massive data, essential for clinical decision-making, patient care, and medical research. Effective management of healthcare data require systems to ensure data integrity, security, regulatory compliance, and interoperability while supporting advanced analytics, predictive modelling, and innovation. Existing healthcare data management systems (DMS) including, centralized, cloud-based, decentralized, integrated, and hybrid systems, are often tailored to specific use-cases and technological frameworks. This paper discusses a general framework for DMS in healthcare and provides a taxonomy of DMSs to help in choosing the right platform for a particular scenario, since there is no “one-size-fits-all” technological solution, especially for healthcare domain dealing with varied and complex data. However, these systems often face challenges related to scalability, security, and interoperability. Recently, blockchain technology has emerged as a potential solution, addressing key issues such as data integrity, data privacy, security, and transparency, ownership, and, access control. Additionally, this paper evaluates suitability of blockchain for addressing healthcare data management challenges and promote blockchain technology adoption in healthcare, alongside AI-powered analytics tools for processing and analysing healthcare big data. The right data management system supported by advanced technologies such as blockchain, AI and ML tools will surely improve healthcare services and promote personalized and precision healthcare.

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