From Data Silos to Interoperable Ecosystems: Challenges and Solutions for EHR/HIE Integration in Digital Health

Abstract

The fragmentation of health data across diverse electronic health record (EHR) systems and health information exchanges (HIEs) remains a major obstacle to delivering coordinated, efficient, and data-driven care. This review provides a comprehensive overview of the current landscape of EHR/HIE integration, examining the technical, organizational, and regulatory factors that continue to hinder interoperability. It highlights three core strategies for overcoming these barriers: the adoption of standardized data models that support consistent semantic and structural representation; the use of API-driven and service-oriented architectures that enable flexible, real-time connectivity; and the application of artificial intelligence techniques for data harmonization, including cleansing, record linkage, and resolution of structural inconsistencies. Beyond technical considerations, the paper also addresses essential issues related to data governance, privacy, security, and policy frameworks that shape the implementation and sustainability of interoperable ecosystems. By synthesizing emerging approaches across these domains, the review outlines a pathway for transitioning from isolated data silos to interconnected digital health infrastructures capable of supporting scalable clinical workflows, improved decision-making, and more integrated patient care. The analysis aims to clarify both the opportunities and challenges involved in achieving meaningful interoperability in contemporary digital health environments.