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Cohort Identification for Clinical Research: Querying Federated Electronic Healthcare Records Using Controlled Vocabularies and Semantic Types

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 investig...

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Detalles Bibliográficos
Autores principales: Lim Choi Keung, Sarah N., Zhao, Lei, Tyler, Edward, Taweel, Adel, Delaney, Brendan, Peterson, Kevin A., Speedie, Stuart M., Richard Hobbs, F.D., Arvanitis, Theodoros N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392063/
https://www.ncbi.nlm.nih.gov/pubmed/22779039
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author Lim Choi Keung, Sarah N.
Zhao, Lei
Tyler, Edward
Taweel, Adel
Delaney, Brendan
Peterson, Kevin A.
Speedie, Stuart M.
Richard Hobbs, F.D.
Arvanitis, Theodoros N.
author_facet Lim Choi Keung, Sarah N.
Zhao, Lei
Tyler, Edward
Taweel, Adel
Delaney, Brendan
Peterson, Kevin A.
Speedie, Stuart M.
Richard Hobbs, F.D.
Arvanitis, Theodoros N.
author_sort Lim Choi Keung, Sarah N.
collection PubMed
description 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.
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spelling pubmed-33920632012-07-09 Cohort Identification for Clinical Research: Querying Federated Electronic Healthcare Records Using Controlled Vocabularies and Semantic Types Lim Choi Keung, Sarah N. Zhao, Lei Tyler, Edward Taweel, Adel Delaney, Brendan Peterson, Kevin A. Speedie, Stuart M. Richard Hobbs, F.D. Arvanitis, Theodoros N. AMIA Jt Summits Transl Sci Proc Articles 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. American Medical Informatics Association 2012-03-19 /pmc/articles/PMC3392063/ /pubmed/22779039 Text en ©2012 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose
spellingShingle Articles
Lim Choi Keung, Sarah N.
Zhao, Lei
Tyler, Edward
Taweel, Adel
Delaney, Brendan
Peterson, Kevin A.
Speedie, Stuart M.
Richard Hobbs, F.D.
Arvanitis, Theodoros N.
Cohort Identification for Clinical Research: Querying Federated Electronic Healthcare Records Using Controlled Vocabularies and Semantic Types
title Cohort Identification for Clinical Research: Querying Federated Electronic Healthcare Records Using Controlled Vocabularies and Semantic Types
title_full Cohort Identification for Clinical Research: Querying Federated Electronic Healthcare Records Using Controlled Vocabularies and Semantic Types
title_fullStr Cohort Identification for Clinical Research: Querying Federated Electronic Healthcare Records Using Controlled Vocabularies and Semantic Types
title_full_unstemmed Cohort Identification for Clinical Research: Querying Federated Electronic Healthcare Records Using Controlled Vocabularies and Semantic Types
title_short Cohort Identification for Clinical Research: Querying Federated Electronic Healthcare Records Using Controlled Vocabularies and Semantic Types
title_sort cohort identification for clinical research: querying federated electronic healthcare records using controlled vocabularies and semantic types
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392063/
https://www.ncbi.nlm.nih.gov/pubmed/22779039
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