Data Lake Governance – Establishing a Single Source of Truth in Healthcare Enterprises

Abstract

Healthcare organizations generate enormous volumes of multi-modal data electronic health records (EHR), pharmacy claims, medical claims, imaging, genomics, IoT sensor streams, and administrative data. However, fragmented systems prevent efficient data sharing, analytics, and decision-making. A well-governed healthcare data lake provides a scalable architecture to integrate structured and unstructured data while maintaining quality, security, and compliance. This paper proposes a comprehensive governance framework enabling a unified Single Source of Truth (SSOT) for healthcare enterprises. The framework integrates metadata management, data lineage, interoperability standards, AI-driven quality checks, and federated access controls. The proposed model ensures trustworthy, timely, and regulated data access for clinical, operational, and financial use cases including population health, pharmacy benefit optimization, risk scoring, and value-based care. The framework further incorporates ethical safeguards to mitigate AI bias, enforce algorithmic fairness, and ensure transparency and accountability in all automated governance decisions