Federated Querying Architecture with Clinical & Translational Health IT Application

Abstract

We present a software architecture that federates data from multiple heterogeneous health informatics data sources owned by multiple organizations. The architecture builds upon state-of-the-art open-source Java and XML frameworks in innovative ways. It consists of (a) federated query engine, which manages federated queries and result set aggregation via a patient identification service; and (b) data source facades, which translate the physical data models into a common model on-the-fly and handle large result set streaming. System modules are connected via reusable Apache Camel integration routes and deployed to an OSGi enterprise service bus. We present an application of our architecture that allows users to construct queries via the i2b2 web front-end, and federates patient data from the University of Utah Enterprise Data Warehouse and the Utah Population database. Our system can be easily adopted, extended and integrated with existing SOA Healthcare and HL7 frameworks such as i2b2 and caGrid.

A Service Oriented Framework to Assess the Quality of Electronic Health Data for Clinical Research

“…The quality assessment framework is a web-service that leverages components within the FURTHeR architecture [2] and can be deployed as a standalone service. The Quality Service (Fig.1) which is the core component can query different data sources irrespective of their data models and local terminology via the FURTHeR system.…”

Information engineering infrastructure for life sciences and its implementation in China

“…The challenges to build such a system lie in subtle balance between search performance and accuracy, and an effective yet friendly interface to navigate search results. Relational Database Management System (RDBMS) does not furnish such a balance when it comes to big data, neither the view-based federated query system [10], nor the metadata-driven system [11]. View-based system is capable of complex cross-database searches.…”

A Focus Area Maturity Model for a Statewide Master Person Index

“…Patient-specific data exchanges are also important for treatment [5] and public health purposes [6] and are increasingly vital for biomedical research. Notable examples include comparative effectiveness and translational research [7], the Shared Health Research Information Network (SHRINE) [8], the cancer Biomedical Informatics Grid (caBIG) [9], and the Federated Utah Research and Translational Health eRepository (FURTHeR) [10]. Emerging infrastructures like these, critically depend on the ability to correctly link patients and their records across heterogeneous electronic systems operated under different administrative domains.…”