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

Nicholas Anderson, Aaron Abend, Aaron Mandel, Estella Geraghty, Davera Gabriel, Rob Wynden, Michael Kamerick, Kent Anderson, Julie Rainwater, Peter Tarczy-Hornoch

Research output: Contribution to journalArticle

17 Citations (Scopus)

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.

Original languageEnglish (US)
JournalJournal of the American Medical Informatics Association
Volume19
Issue numberE1
DOIs
StatePublished - Jun 2012
Externally publishedYes

Fingerprint

Translational Medical Research
Software
Population
Informatics
San Francisco
Semantics
Clinical Trials
Research
Datasets

ASJC Scopus subject areas

  • Health Informatics

Cite this

Implementation of a deidentified federated data network for population-based cohort discovery. / Anderson, Nicholas; Abend, Aaron; Mandel, Aaron; Geraghty, Estella; Gabriel, Davera; Wynden, Rob; Kamerick, Michael; Anderson, Kent; Rainwater, Julie; Tarczy-Hornoch, Peter.

In: Journal of the American Medical Informatics Association, Vol. 19, No. E1, 06.2012.

Research output: Contribution to journalArticle

Anderson, N, Abend, A, Mandel, A, Geraghty, E, Gabriel, D, Wynden, R, Kamerick, M, Anderson, K, Rainwater, J & Tarczy-Hornoch, P 2012, 'Implementation of a deidentified federated data network for population-based cohort discovery', Journal of the American Medical Informatics Association, vol. 19, no. E1. https://doi.org/10.1136/amiajnl-2011-000133
Anderson, Nicholas ; Abend, Aaron ; Mandel, Aaron ; Geraghty, Estella ; Gabriel, Davera ; Wynden, Rob ; Kamerick, Michael ; Anderson, Kent ; Rainwater, Julie ; Tarczy-Hornoch, Peter. / Implementation of a deidentified federated data network for population-based cohort discovery. In: Journal of the American Medical Informatics Association. 2012 ; Vol. 19, No. E1.
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