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LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing
The University of Washington Institute of Translational Health Sciences is engaged in a project, LC Data QUEST, building data sharing capacity in primary care practices serving rural and tribal populations in the Washington, Wyoming, Alaska, Montana, Idaho region to build research infrastructure. We...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Informatics Association
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392065/ https://www.ncbi.nlm.nih.gov/pubmed/22779052 |
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author | Stephens, Kari A. Lin, Ching-Ping Baldwin, Laura-Mae Echo-Hawk, Abigail Keppel, Gina A. Buchwald, Dedra Whitener, Ron J. Korngiebel, Diane M. Berg, Alfred O. Black, Robert A. Tarczy-Hornoch, Peter |
author_facet | Stephens, Kari A. Lin, Ching-Ping Baldwin, Laura-Mae Echo-Hawk, Abigail Keppel, Gina A. Buchwald, Dedra Whitener, Ron J. Korngiebel, Diane M. Berg, Alfred O. Black, Robert A. Tarczy-Hornoch, Peter |
author_sort | Stephens, Kari A. |
collection | PubMed |
description | The University of Washington Institute of Translational Health Sciences is engaged in a project, LC Data QUEST, building data sharing capacity in primary care practices serving rural and tribal populations in the Washington, Wyoming, Alaska, Montana, Idaho region to build research infrastructure. We report on the iterative process of developing the technical architecture for semantically aligning electronic health data in primary care settings across our pilot sites and tools that will facilitate linkages between the research and practice communities. Our architecture emphasizes sustainable technical solutions for addressing data extraction, alignment, quality, and metadata management. The architecture provides immediate benefits to participating partners via a clinical decision support tool and data querying functionality to support local quality improvement efforts. The FInDiT tool catalogues type, quantity, and quality of the data that are available across the LC Data QUEST data sharing architecture. These tools facilitate the bi-directional process of translational research. |
format | Online Article Text |
id | pubmed-3392065 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | American Medical Informatics Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-33920652012-07-09 LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing Stephens, Kari A. Lin, Ching-Ping Baldwin, Laura-Mae Echo-Hawk, Abigail Keppel, Gina A. Buchwald, Dedra Whitener, Ron J. Korngiebel, Diane M. Berg, Alfred O. Black, Robert A. Tarczy-Hornoch, Peter AMIA Jt Summits Transl Sci Proc Articles The University of Washington Institute of Translational Health Sciences is engaged in a project, LC Data QUEST, building data sharing capacity in primary care practices serving rural and tribal populations in the Washington, Wyoming, Alaska, Montana, Idaho region to build research infrastructure. We report on the iterative process of developing the technical architecture for semantically aligning electronic health data in primary care settings across our pilot sites and tools that will facilitate linkages between the research and practice communities. Our architecture emphasizes sustainable technical solutions for addressing data extraction, alignment, quality, and metadata management. The architecture provides immediate benefits to participating partners via a clinical decision support tool and data querying functionality to support local quality improvement efforts. The FInDiT tool catalogues type, quantity, and quality of the data that are available across the LC Data QUEST data sharing architecture. These tools facilitate the bi-directional process of translational research. American Medical Informatics Association 2012-03-19 /pmc/articles/PMC3392065/ /pubmed/22779052 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 Stephens, Kari A. Lin, Ching-Ping Baldwin, Laura-Mae Echo-Hawk, Abigail Keppel, Gina A. Buchwald, Dedra Whitener, Ron J. Korngiebel, Diane M. Berg, Alfred O. Black, Robert A. Tarczy-Hornoch, Peter LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing |
title | LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing |
title_full | LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing |
title_fullStr | LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing |
title_full_unstemmed | LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing |
title_short | LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing |
title_sort | lc data quest: a technical architecture for community federated clinical data sharing |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392065/ https://www.ncbi.nlm.nih.gov/pubmed/22779052 |
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