Tissue-to-Bytes: A Catalytic Digital Twin Platform for Consortium-Scale Integration of Single-Cell Omics Data in BRAIN Initiative Cell Atlas Network
Monolithic Electronic Health Record (EHR) architectures remain fundamentally misaligned with high-resolution, specialty-specific clinical workflows, contributing to significant physician burnout and challangies in secondary use of data. This study introduces the Enterprise Health Twin (EHT) framework, a paradigm grounded in the Digital Twin concept, with the goal to transform static clinical ledgers into dynamic decision-support systems. The EHT establishes continuous bidirectional feedback (feed-forward ingestion and feed-backward decision support) between the physical entities of clinical workflows and the digital counterparts of interfaces reflecting the evolving states of the workflow, for each individual patient in the EHT. We conceptualized, prototyped, and operationalized the EHT framework for epilepsy care for seven years, in production, at the point of care. Deployed at the Epilepsy Center of the University of Texas Health Science Center at Houston, a [~]400% increase productivity has been achieved in specialized surgical evaluation throughput without additional staffing. The EHT achieved de novo capture of ontology-anchored structured data at the point of care, mitigating cognitive load while growing the volume of high-resolution, annotated longitudinal datasets for clinical research, and driving an increase of care velocity in a learning healthcare system.