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Whatever can go wrong, need not go wrong: Open Quality approach for epidemiology

Quality assurance is one of the most important aspects of an epidemiological study, as its validity is largely determined by data quality. The mounting success of quality management in the industrial sector caused a rapid spread throughout manufacturing industries and beyond. Yet, little has been pu...

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Autores principales: Alba, Sandra, Straetemans, Masja
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8285770/
https://www.ncbi.nlm.nih.gov/pubmed/34273982
http://dx.doi.org/10.1186/s12982-021-00098-0
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author Alba, Sandra
Straetemans, Masja
author_facet Alba, Sandra
Straetemans, Masja
author_sort Alba, Sandra
collection PubMed
description Quality assurance is one of the most important aspects of an epidemiological study, as its validity is largely determined by data quality. The mounting success of quality management in the industrial sector caused a rapid spread throughout manufacturing industries and beyond. Yet, little has been published so far on quality assurance in epidemiology. In this article we review three models for quality assurance (Juran, Donabedian and ISO 9000) and showcase how these can be brought together in one intuitive, systematic and flexible approach to quality assurance in epidemiology. The resulting Open Quality approach refers back to the three processes identified by Juran (planning, control and verification). During the planning stage, we propose a subdivision of the study process in a set of steps and a definition of quality attributes corresponding to activities in that step as suggested by the ISO approach. We refer to the Donabedian model to determine the level at which the control/monitoring should take place—structure, processes or outcomes. Along with an overview of the Open Quality approach we propose an Open Quality tool to support the definition of quality attributes, failure modes, preventive strategies, verification activities, and corrective actions, which form the backbone of the Open Quality approach. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12982-021-00098-0.
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spelling pubmed-82857702021-07-19 Whatever can go wrong, need not go wrong: Open Quality approach for epidemiology Alba, Sandra Straetemans, Masja Emerg Themes Epidemiol Analytic Perspective Quality assurance is one of the most important aspects of an epidemiological study, as its validity is largely determined by data quality. The mounting success of quality management in the industrial sector caused a rapid spread throughout manufacturing industries and beyond. Yet, little has been published so far on quality assurance in epidemiology. In this article we review three models for quality assurance (Juran, Donabedian and ISO 9000) and showcase how these can be brought together in one intuitive, systematic and flexible approach to quality assurance in epidemiology. The resulting Open Quality approach refers back to the three processes identified by Juran (planning, control and verification). During the planning stage, we propose a subdivision of the study process in a set of steps and a definition of quality attributes corresponding to activities in that step as suggested by the ISO approach. We refer to the Donabedian model to determine the level at which the control/monitoring should take place—structure, processes or outcomes. Along with an overview of the Open Quality approach we propose an Open Quality tool to support the definition of quality attributes, failure modes, preventive strategies, verification activities, and corrective actions, which form the backbone of the Open Quality approach. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12982-021-00098-0. BioMed Central 2021-07-17 /pmc/articles/PMC8285770/ /pubmed/34273982 http://dx.doi.org/10.1186/s12982-021-00098-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Analytic Perspective
Alba, Sandra
Straetemans, Masja
Whatever can go wrong, need not go wrong: Open Quality approach for epidemiology
title Whatever can go wrong, need not go wrong: Open Quality approach for epidemiology
title_full Whatever can go wrong, need not go wrong: Open Quality approach for epidemiology
title_fullStr Whatever can go wrong, need not go wrong: Open Quality approach for epidemiology
title_full_unstemmed Whatever can go wrong, need not go wrong: Open Quality approach for epidemiology
title_short Whatever can go wrong, need not go wrong: Open Quality approach for epidemiology
title_sort whatever can go wrong, need not go wrong: open quality approach for epidemiology
topic Analytic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8285770/
https://www.ncbi.nlm.nih.gov/pubmed/34273982
http://dx.doi.org/10.1186/s12982-021-00098-0
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