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DQAgui: a graphical user interface for the MIRACUM data quality assessment tool

BACKGROUND: With the growing impact of observational research studies, there is also a growing focus on data quality (DQ). As opposed to experimental study designs, observational research studies are performed using data mostly collected in a non-research context (secondary use). Depending on the nu...

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Autores principales: Mang, Jonathan M., Seuchter, Susanne A., Gulden, Christian, Schild, Stefanie, Kraska, Detlef, Prokosch, Hans-Ulrich, Kapsner, Lorenz A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9367129/
https://www.ncbi.nlm.nih.gov/pubmed/35953813
http://dx.doi.org/10.1186/s12911-022-01961-z
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author Mang, Jonathan M.
Seuchter, Susanne A.
Gulden, Christian
Schild, Stefanie
Kraska, Detlef
Prokosch, Hans-Ulrich
Kapsner, Lorenz A.
author_facet Mang, Jonathan M.
Seuchter, Susanne A.
Gulden, Christian
Schild, Stefanie
Kraska, Detlef
Prokosch, Hans-Ulrich
Kapsner, Lorenz A.
author_sort Mang, Jonathan M.
collection PubMed
description BACKGROUND: With the growing impact of observational research studies, there is also a growing focus on data quality (DQ). As opposed to experimental study designs, observational research studies are performed using data mostly collected in a non-research context (secondary use). Depending on the number of data elements to be analyzed, DQ reports of data stored within research networks can grow very large. They might be cumbersome to read and important information could be overseen quickly. To address this issue, a DQ assessment (DQA) tool with a graphical user interface (GUI) was developed and provided as a web application. METHODS: The aim was to provide an easy-to-use interface for users without prior programming knowledge to carry out DQ checks and to present the results in a clearly structured way. This interface serves as a starting point for a more detailed investigation of possible DQ irregularities. A user-centered development process ensured the practical feasibility of the interactive GUI. The interface was implemented in the R programming language and aligned to Kahn et al.’s DQ categories conformance, completeness and plausibility. RESULTS: With DQAgui, an R package with a web-app frontend for DQ assessment was developed. The GUI allows users to perform DQ analyses of tabular data sets and to systematically evaluate the results. During the development of the GUI, additional features were implemented, such as analyzing a subset of the data by defining time periods and restricting the analyses to certain data elements. CONCLUSIONS: As part of the MIRACUM project, DQAgui is now being used at ten German university hospitals for DQ assessment and to provide a central overview of the availability of important data elements in a datamap over 2 years. Future development efforts should focus on design optimization and include a usability evaluation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-022-01961-z.
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spelling pubmed-93671292022-08-12 DQAgui: a graphical user interface for the MIRACUM data quality assessment tool Mang, Jonathan M. Seuchter, Susanne A. Gulden, Christian Schild, Stefanie Kraska, Detlef Prokosch, Hans-Ulrich Kapsner, Lorenz A. BMC Med Inform Decis Mak Research BACKGROUND: With the growing impact of observational research studies, there is also a growing focus on data quality (DQ). As opposed to experimental study designs, observational research studies are performed using data mostly collected in a non-research context (secondary use). Depending on the number of data elements to be analyzed, DQ reports of data stored within research networks can grow very large. They might be cumbersome to read and important information could be overseen quickly. To address this issue, a DQ assessment (DQA) tool with a graphical user interface (GUI) was developed and provided as a web application. METHODS: The aim was to provide an easy-to-use interface for users without prior programming knowledge to carry out DQ checks and to present the results in a clearly structured way. This interface serves as a starting point for a more detailed investigation of possible DQ irregularities. A user-centered development process ensured the practical feasibility of the interactive GUI. The interface was implemented in the R programming language and aligned to Kahn et al.’s DQ categories conformance, completeness and plausibility. RESULTS: With DQAgui, an R package with a web-app frontend for DQ assessment was developed. The GUI allows users to perform DQ analyses of tabular data sets and to systematically evaluate the results. During the development of the GUI, additional features were implemented, such as analyzing a subset of the data by defining time periods and restricting the analyses to certain data elements. CONCLUSIONS: As part of the MIRACUM project, DQAgui is now being used at ten German university hospitals for DQ assessment and to provide a central overview of the availability of important data elements in a datamap over 2 years. Future development efforts should focus on design optimization and include a usability evaluation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12911-022-01961-z. BioMed Central 2022-08-11 /pmc/articles/PMC9367129/ /pubmed/35953813 http://dx.doi.org/10.1186/s12911-022-01961-z Text en © The Author(s) 2022 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 Research
Mang, Jonathan M.
Seuchter, Susanne A.
Gulden, Christian
Schild, Stefanie
Kraska, Detlef
Prokosch, Hans-Ulrich
Kapsner, Lorenz A.
DQAgui: a graphical user interface for the MIRACUM data quality assessment tool
title DQAgui: a graphical user interface for the MIRACUM data quality assessment tool
title_full DQAgui: a graphical user interface for the MIRACUM data quality assessment tool
title_fullStr DQAgui: a graphical user interface for the MIRACUM data quality assessment tool
title_full_unstemmed DQAgui: a graphical user interface for the MIRACUM data quality assessment tool
title_short DQAgui: a graphical user interface for the MIRACUM data quality assessment tool
title_sort dqagui: a graphical user interface for the miracum data quality assessment tool
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9367129/
https://www.ncbi.nlm.nih.gov/pubmed/35953813
http://dx.doi.org/10.1186/s12911-022-01961-z
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