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AMIA Summits Transl Sci Proc. 2012; 2012: 9.
Published online Mar 19, 2012.
PMCID: PMC3392063
Cohort Identification for Clinical Research: Querying Federated Electronic Healthcare Records Using Controlled Vocabularies and Semantic Types
Sarah N. Lim Choi Keung, PhD,1 Lei Zhao, MSc,1 Edward Tyler, MSc,1 Adel Taweel, PhD,2 Brendan Delaney, MD,2 Kevin A. Peterson, MD, MPH,3 Stuart M. Speedie, PhD,3 F.D. Richard Hobbs, MB ChB,4 and Theodoros N. Arvanitis, DPhil1
1University of Birmingham, United Kingdom;
2King’s College London, United Kingdom;
3University of Minnesota, Minneapolis, MN;
4University of Oxford, United Kingdom
In the United Kingdom (UK), local initiatives have started to federate electronic healthcare records from different primary care clinical systems, mainly for the purposes of ensuring that health care services effectively meet the needs of the population. The use of such information is being investigated for clinical research, notably in patient cohort identification and recruitment. To achieve these aims, it is essential that the information from different systems can be searched from a single interface. While interoperability is a widely researched topic, interoperable methods and data sources in primary care are largely missing. This paper describes our approach to enabling primary care data in England to be searchable on a platform developed for performing large national collaborative primary care research studies throughout the United States.
Articles from AMIA Summits on Translational Science Proceedings are provided here courtesy of
American Medical Informatics Association