Big Data Governance in Healthcare Institutions: A Systematic Review and Implications for Tanzania

Abstract

Background and Purpose: The rapid adoption of digital health technologies has led to unprecedented growth in healthcare data, commonly referred to as big data. To guarantee data quality, privacy protection, and trustworthy decision-making within healthcare organizations, this data must be governed effectively in nexus with context-aware aspects.

Methods: This paper adopts systematically literature reviews (SLR) to synthesize relevant literature on big data governance in healthcare, with an emphasis on the implications for Tanzanian healthcare system context. The review synthesizes studies from various academic databases that were published between 2010 and 2025.

Results: The results show that important data governance elements, including data quality, privacy and security, interoperability, and regulatory compliance, are the main focus of current healthcare big data governance frameworks. Despite these developments, most data governance frameworks are conceptual, designed for healthcare settings with ample resources and often fall short of addressing the contextual issues that arise in resource-constrained settings.

Conclusion: This study proposes a context-aware big data governance context-aware conceptual model, identifies critical gaps in the current literature, and highlights the need for context-aware governance approaches. It further outlines implications for Tanzania’s healthcare system adoption, providing a foundation for the development of tailored big data governance frameworks suitable for resource-constrained healthcare systems