Implementation of a deidentified federated data network for population-based cohort discovery

Abstract

Objective: The Cross-Institutional Clinical Translational Research project explored a federated query tool and looked at how this tool can facilitate clinical trial cohort discovery by managing access to aggregate patient data located within unaffiliated academic medical centers.

Methods: The project adapted software from the Informatics for Integrating Biology and the Bedside (i2b2) program to connect three Clinical Translational Research Award sites: University of Washington, Seattle, University of California, Davis, and University of California, San Francisco. The project developed an iterative spiral software development model to support the implementation and coordination of this multisite data resource.

Results: By standardizing technical infrastructures, policies, and semantics, the project enabled federated querying of deidentified clinical datasets stored in separate institutional environments and identified barriers to engaging users for measuring utility.

Discussion: The authors discuss the iterative development and evaluation phases of the project and highlight the challenges identified and the lessons learned.

Conclusion: The common system architecture and translational processes provide high-level (aggregate) deidentified access to a large patient population (>5 million patients), and represent a novel and extensible resource. Enhancing the network for more focused disease areas will require research-driven partnerships represented across all partner sites.

Figure 1

Cross-Institutional Clinical Translational Research (CICTR) network security diagram (simplified) describing isolation of Shared Health Research Information Network (SHRINE) cells from direct access to i2b2 data repositories. CICTR, Cross-Institutional Clinical Translational Research project; DMZ, Demilitarized Zone; IP, Internet Protocol; JDBC, Java Database Connectivity; SSL, Secure Sockets Layer; UCSF, University of California, San Francisco; UW, University of Washington; VLAN, Virtual Local Area Network; VPN, Virtual Private Network.

Figure 2

Local site-coordinated data loading, deidentification, and mapping processes.

Figure 3

Return of aggregated and blurred results across Cross-Institutional Clinical Translational Research (CICTR) network.

Figure 4

Descriptive spiral model of implementation phases and stakeholders. CER, Comparative Effectiveness Research; ETL, Extraction, Transformation and Loading SHRINE - Shared Health Research Information Network; IRB, Institutional Review Board; i2b2, Informatics for Integrating Biology and the Bedside