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Improving a Secondary Use Health Data Warehouse: Proposing a Multi-Level Data Quality Framework
BACKGROUND: Data quality frameworks within information technology and recently within health care have evolved considerably since their inception. When assessing data quality for secondary uses, an area not yet addressed adequately in these frameworks is the context of the intended use of the data....
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ubiquity Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6676919/ https://www.ncbi.nlm.nih.gov/pubmed/31531384 http://dx.doi.org/10.5334/egems.298 |
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author | Henley-Smith, Sandra Boyle, Douglas Gray, Kathleen |
author_facet | Henley-Smith, Sandra Boyle, Douglas Gray, Kathleen |
author_sort | Henley-Smith, Sandra |
collection | PubMed |
description | BACKGROUND: Data quality frameworks within information technology and recently within health care have evolved considerably since their inception. When assessing data quality for secondary uses, an area not yet addressed adequately in these frameworks is the context of the intended use of the data. METHODS: After review of literature to identify relevant research, an existing data quality framework was refined and expanded to encompass the contextual requirements not present. RESULTS: The result is a two-level framework to address the need to maintain the intrinsic value of the data, as well as the need to indicate whether the data will be able to provide the basis for answers in specific areas of interest or questions. DISCUSSION: Data quality frameworks have always been one dimensional, requiring the implementers of these frameworks to fit the requirements of the data’s use around how the framework is designed to function. Our work has systematically addressed the shortcomings of existing frameworks, through the application of concepts synthesized from the literature to the naturalistic setting of data quality management in an actual health data warehouse. CONCLUSION: Secondary use of health data relies on contextualized data quality management. Our work is innovative in showing how to apply context around data quality characteristics and how to develop a second level data quality framework, so as to ensure that quality and context are maintained and addressed throughout the health data quality assessment process. |
format | Online Article Text |
id | pubmed-6676919 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Ubiquity Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-66769192019-09-17 Improving a Secondary Use Health Data Warehouse: Proposing a Multi-Level Data Quality Framework Henley-Smith, Sandra Boyle, Douglas Gray, Kathleen EGEMS (Wash DC) Model/Framework BACKGROUND: Data quality frameworks within information technology and recently within health care have evolved considerably since their inception. When assessing data quality for secondary uses, an area not yet addressed adequately in these frameworks is the context of the intended use of the data. METHODS: After review of literature to identify relevant research, an existing data quality framework was refined and expanded to encompass the contextual requirements not present. RESULTS: The result is a two-level framework to address the need to maintain the intrinsic value of the data, as well as the need to indicate whether the data will be able to provide the basis for answers in specific areas of interest or questions. DISCUSSION: Data quality frameworks have always been one dimensional, requiring the implementers of these frameworks to fit the requirements of the data’s use around how the framework is designed to function. Our work has systematically addressed the shortcomings of existing frameworks, through the application of concepts synthesized from the literature to the naturalistic setting of data quality management in an actual health data warehouse. CONCLUSION: Secondary use of health data relies on contextualized data quality management. Our work is innovative in showing how to apply context around data quality characteristics and how to develop a second level data quality framework, so as to ensure that quality and context are maintained and addressed throughout the health data quality assessment process. Ubiquity Press 2019-08-02 /pmc/articles/PMC6676919/ /pubmed/31531384 http://dx.doi.org/10.5334/egems.298 Text en Copyright: © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Model/Framework Henley-Smith, Sandra Boyle, Douglas Gray, Kathleen Improving a Secondary Use Health Data Warehouse: Proposing a Multi-Level Data Quality Framework |
title | Improving a Secondary Use Health Data Warehouse: Proposing a Multi-Level Data Quality Framework |
title_full | Improving a Secondary Use Health Data Warehouse: Proposing a Multi-Level Data Quality Framework |
title_fullStr | Improving a Secondary Use Health Data Warehouse: Proposing a Multi-Level Data Quality Framework |
title_full_unstemmed | Improving a Secondary Use Health Data Warehouse: Proposing a Multi-Level Data Quality Framework |
title_short | Improving a Secondary Use Health Data Warehouse: Proposing a Multi-Level Data Quality Framework |
title_sort | improving a secondary use health data warehouse: proposing a multi-level data quality framework |
topic | Model/Framework |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6676919/ https://www.ncbi.nlm.nih.gov/pubmed/31531384 http://dx.doi.org/10.5334/egems.298 |
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