Toward High-Fidelity Healthcare Digital Twins: Integrating Real-Time Processing, Data Mesh, and MDM (Published)
Healthcare digital twins are emerging as powerful tools for simulating patient conditions and operational workflows in real time. This paper explores the architectural and technical foundation necessary for building high-fidelity digital twins—those capable of accurate, synchronized, and responsive modeling. It identifies key challenges, including fragmented data, latency, poor semantic alignment, and identity inconsistencies. To overcome these, the study proposes a five-layer architecture integrating real-time data processing, data mesh principles, and master data management (MDM). Through case studies involving heart failure monitoring and hospital operations, the research demonstrates improvements in fidelity, latency, and interoperability. The study concludes with strategic guidance for healthcare organizations and outlines future research topics, including automated twin generation and federated implementations. By aligning infrastructure with intelligence, the proposed model advances the promise of high-fidelity digital twins from concept to clinical reality.
Keywords: Digital twin, Healthcare, data mesh, master data management (MDM), real-time processing
Unifying Healthcare Through MDM: Paving the Way for Precision Medicine and Population Health (Published)
As healthcare systems generate increasingly complex datasets, from EHRs and genomic profiles to social and behavioral determinants, the need for an integrated, reliable data infrastructure has never been greater. This paper explores the critical role of Master Data Management (MDM) in addressing fragmentation and inconsistency in healthcare data, and its strategic application in advancing both precision medicine and population health. Through a synthesis of peer-reviewed research, industry case studies, and regulatory frameworks, the study demonstrates how MDM enables accurate patient identity resolution, data standardization, and semantic interoperability. These capabilities support the creation of unified patient records, which serve as the foundation for individualized treatment plans, chronic disease surveillance, and targeted public health interventions. The findings underscore MDM’s transition from a backend data utility to a strategic enabler of personalized and population-wide care.
Keywords: Healthcare, master data management (MDM), patient 360-degree view, population health, precision medicine