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Detailed Clinical Modelling Approach to Data Extraction from Heterogeneous Data Sources for Clinical Research
The reuse of routinely collected clinical data for clinical research is being explored as part of the drive to reduce duplicate data entry and to start making full use of the big data potential in the healthcare domain. Clinical researchers often need to extract data from patient registries and othe...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Medical Informatics Association
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4419774/ https://www.ncbi.nlm.nih.gov/pubmed/25954578 |
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author | Lim Choi Keung, Sarah N. Zhao, Lei Rossiter, James McGilchrist, Mark Culross, Frank Ethier, Jean-François Burgun, Anita Verheij, Robert A. Khan, Nasra Taweel, Adel Curcin, Vasa Delaney, Brendan C. Arvanitis, Theodoros N. |
author_facet | Lim Choi Keung, Sarah N. Zhao, Lei Rossiter, James McGilchrist, Mark Culross, Frank Ethier, Jean-François Burgun, Anita Verheij, Robert A. Khan, Nasra Taweel, Adel Curcin, Vasa Delaney, Brendan C. Arvanitis, Theodoros N. |
author_sort | Lim Choi Keung, Sarah N. |
collection | PubMed |
description | The reuse of routinely collected clinical data for clinical research is being explored as part of the drive to reduce duplicate data entry and to start making full use of the big data potential in the healthcare domain. Clinical researchers often need to extract data from patient registries and other patient record datasets for data analysis as part of clinical studies. In the TRANSFoRm project, researchers define their study requirements via a Query Formulation Workbench. We use a standardised approach to data extraction to retrieve relevant information from heterogeneous data sources, using semantic interoperability enabled via detailed clinical modelling. This approach is used for data extraction from data sources for analysis and for pre-population of electronic Case Report Forms from electronic health records in primary care clinical systems. |
format | Online Article Text |
id | pubmed-4419774 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | American Medical Informatics Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-44197742015-05-07 Detailed Clinical Modelling Approach to Data Extraction from Heterogeneous Data Sources for Clinical Research Lim Choi Keung, Sarah N. Zhao, Lei Rossiter, James McGilchrist, Mark Culross, Frank Ethier, Jean-François Burgun, Anita Verheij, Robert A. Khan, Nasra Taweel, Adel Curcin, Vasa Delaney, Brendan C. Arvanitis, Theodoros N. AMIA Jt Summits Transl Sci Proc Articles The reuse of routinely collected clinical data for clinical research is being explored as part of the drive to reduce duplicate data entry and to start making full use of the big data potential in the healthcare domain. Clinical researchers often need to extract data from patient registries and other patient record datasets for data analysis as part of clinical studies. In the TRANSFoRm project, researchers define their study requirements via a Query Formulation Workbench. We use a standardised approach to data extraction to retrieve relevant information from heterogeneous data sources, using semantic interoperability enabled via detailed clinical modelling. This approach is used for data extraction from data sources for analysis and for pre-population of electronic Case Report Forms from electronic health records in primary care clinical systems. American Medical Informatics Association 2014-04-07 /pmc/articles/PMC4419774/ /pubmed/25954578 Text en ©2014 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 Rossiter, James McGilchrist, Mark Culross, Frank Ethier, Jean-François Burgun, Anita Verheij, Robert A. Khan, Nasra Taweel, Adel Curcin, Vasa Delaney, Brendan C. Arvanitis, Theodoros N. Detailed Clinical Modelling Approach to Data Extraction from Heterogeneous Data Sources for Clinical Research |
title | Detailed Clinical Modelling Approach to Data Extraction from Heterogeneous Data Sources for Clinical Research |
title_full | Detailed Clinical Modelling Approach to Data Extraction from Heterogeneous Data Sources for Clinical Research |
title_fullStr | Detailed Clinical Modelling Approach to Data Extraction from Heterogeneous Data Sources for Clinical Research |
title_full_unstemmed | Detailed Clinical Modelling Approach to Data Extraction from Heterogeneous Data Sources for Clinical Research |
title_short | Detailed Clinical Modelling Approach to Data Extraction from Heterogeneous Data Sources for Clinical Research |
title_sort | detailed clinical modelling approach to data extraction from heterogeneous data sources for clinical research |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4419774/ https://www.ncbi.nlm.nih.gov/pubmed/25954578 |
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