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Validation of multisource electronic health record data: an application to blood transfusion data
BACKGROUND: Although data from electronic health records (EHR) are often used for research purposes, systematic validation of these data prior to their use is not standard practice. Existing validation frameworks discuss validity concepts without translating these into practical implementation steps...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5512751/ https://www.ncbi.nlm.nih.gov/pubmed/28709453 http://dx.doi.org/10.1186/s12911-017-0504-7 |
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author | Hoeven, Loan R. van Bruijne, Martine C. de Kemper, Peter F. Koopman, Maria M.W. Rondeel, Jan M.M. Leyte, Anja Koffijberg, Hendrik Janssen, Mart P. Roes, Kit C.B. |
author_facet | Hoeven, Loan R. van Bruijne, Martine C. de Kemper, Peter F. Koopman, Maria M.W. Rondeel, Jan M.M. Leyte, Anja Koffijberg, Hendrik Janssen, Mart P. Roes, Kit C.B. |
author_sort | Hoeven, Loan R. van |
collection | PubMed |
description | BACKGROUND: Although data from electronic health records (EHR) are often used for research purposes, systematic validation of these data prior to their use is not standard practice. Existing validation frameworks discuss validity concepts without translating these into practical implementation steps or addressing the potential influence of linking multiple sources. Therefore we developed a practical approach for validating routinely collected data from multiple sources and to apply it to a blood transfusion data warehouse to evaluate the usability in practice. METHODS: The approach consists of identifying existing validation frameworks for EHR data or linked data, selecting validity concepts from these frameworks and establishing quantifiable validity outcomes for each concept. The approach distinguishes external validation concepts (e.g. concordance with external reports, previous literature and expert feedback) and internal consistency concepts which use expected associations within the dataset itself (e.g. completeness, uniformity and plausibility). In an example case, the selected concepts were applied to a transfusion dataset and specified in more detail. RESULTS: Application of the approach to a transfusion dataset resulted in a structured overview of data validity aspects. This allowed improvement of these aspects through further processing of the data and in some cases adjustment of the data extraction. For example, the proportion of transfused products that could not be linked to the corresponding issued products initially was 2.2% but could be improved by adjusting data extraction criteria to 0.17%. CONCLUSIONS: This stepwise approach for validating linked multisource data provides a basis for evaluating data quality and enhancing interpretation. When the process of data validation is adopted more broadly, this contributes to increased transparency and greater reliability of research based on routinely collected electronic health records. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12911-017-0504-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5512751 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-55127512017-07-19 Validation of multisource electronic health record data: an application to blood transfusion data Hoeven, Loan R. van Bruijne, Martine C. de Kemper, Peter F. Koopman, Maria M.W. Rondeel, Jan M.M. Leyte, Anja Koffijberg, Hendrik Janssen, Mart P. Roes, Kit C.B. BMC Med Inform Decis Mak Research Article BACKGROUND: Although data from electronic health records (EHR) are often used for research purposes, systematic validation of these data prior to their use is not standard practice. Existing validation frameworks discuss validity concepts without translating these into practical implementation steps or addressing the potential influence of linking multiple sources. Therefore we developed a practical approach for validating routinely collected data from multiple sources and to apply it to a blood transfusion data warehouse to evaluate the usability in practice. METHODS: The approach consists of identifying existing validation frameworks for EHR data or linked data, selecting validity concepts from these frameworks and establishing quantifiable validity outcomes for each concept. The approach distinguishes external validation concepts (e.g. concordance with external reports, previous literature and expert feedback) and internal consistency concepts which use expected associations within the dataset itself (e.g. completeness, uniformity and plausibility). In an example case, the selected concepts were applied to a transfusion dataset and specified in more detail. RESULTS: Application of the approach to a transfusion dataset resulted in a structured overview of data validity aspects. This allowed improvement of these aspects through further processing of the data and in some cases adjustment of the data extraction. For example, the proportion of transfused products that could not be linked to the corresponding issued products initially was 2.2% but could be improved by adjusting data extraction criteria to 0.17%. CONCLUSIONS: This stepwise approach for validating linked multisource data provides a basis for evaluating data quality and enhancing interpretation. When the process of data validation is adopted more broadly, this contributes to increased transparency and greater reliability of research based on routinely collected electronic health records. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12911-017-0504-7) contains supplementary material, which is available to authorized users. BioMed Central 2017-07-14 /pmc/articles/PMC5512751/ /pubmed/28709453 http://dx.doi.org/10.1186/s12911-017-0504-7 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Hoeven, Loan R. van Bruijne, Martine C. de Kemper, Peter F. Koopman, Maria M.W. Rondeel, Jan M.M. Leyte, Anja Koffijberg, Hendrik Janssen, Mart P. Roes, Kit C.B. Validation of multisource electronic health record data: an application to blood transfusion data |
title | Validation of multisource electronic health record data: an application to blood transfusion data |
title_full | Validation of multisource electronic health record data: an application to blood transfusion data |
title_fullStr | Validation of multisource electronic health record data: an application to blood transfusion data |
title_full_unstemmed | Validation of multisource electronic health record data: an application to blood transfusion data |
title_short | Validation of multisource electronic health record data: an application to blood transfusion data |
title_sort | validation of multisource electronic health record data: an application to blood transfusion data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5512751/ https://www.ncbi.nlm.nih.gov/pubmed/28709453 http://dx.doi.org/10.1186/s12911-017-0504-7 |
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