Advancing Healthcare Interoperability Through Business Analytics and Comparative Evaluation of MIHIN and NHS Data Ecosystems

Abstract

Healthcare interoperability remains a critical challenge in achieving efficient, patient-centered, and data-driven health systems globally. This study explores how business analytics can advance healthcare interoperability by examining and comparing the data ecosystems of the Michigan Health Information Network (MIHIN) and the United Kingdom’s National Health Service (NHS). The paper highlights the strategic role of interoperable data infrastructures in enhancing clinical decision- making, care coordination, population health management, and system efficiency. It discusses how business analytics enables the transformation of fragmented health data into actionable insights, supporting value-based care and improved health outcomes. Through a comparative perspective, the study identifies key strengths, governance structures, data integration frameworks, and policy environments that shape interoperability performance in both MIHIN and the NHS. The analysis Highlights the importance of standardized data exchange, robust analytics capabilities, stakeholder collaboration, and regulatory alignment in sustaining interoperable health ecosystems. By contrasting a decentralized, state-driven model with a centralized national health system, the paper reveals transferable lessons and best practices relevant to both developed and developing healthcare systems. The findings contribute to the growing discourse on digital health transformation by emphasizing the synergy between business analytics and interoperability as a foundation for resilient, efficient, and scalable healthcare systems. This study provides valuable insights for policymakers, healthcare administrators, and digital health stakeholders seeking to strengthen data-driven healthcare delivery and cross-system integration.