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Research and Exploratory Analysis Driven—Time-data Visualization (read-tv) software

MOTIVATION: Research & Exploratory Analysis Driven Time-data Visualization (read-tv) is an open source R Shiny application for visualizing irregularly and regularly spaced longitudinal data. read-tv provides unique filtering and changepoint analysis (CPA) features. The need for these analyses wa...

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Detalles Bibliográficos
Autores principales: Del Gaizo, John, Catchpole, Ken R, Alekseyenko, Alexander V
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935610/
https://www.ncbi.nlm.nih.gov/pubmed/33709063
http://dx.doi.org/10.1093/jamiaopen/ooab007
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author Del Gaizo, John
Catchpole, Ken R
Alekseyenko, Alexander V
author_facet Del Gaizo, John
Catchpole, Ken R
Alekseyenko, Alexander V
author_sort Del Gaizo, John
collection PubMed
description MOTIVATION: Research & Exploratory Analysis Driven Time-data Visualization (read-tv) is an open source R Shiny application for visualizing irregularly and regularly spaced longitudinal data. read-tv provides unique filtering and changepoint analysis (CPA) features. The need for these analyses was motivated by research of surgical work-flow disruptions in operating room settings. Specifically, for the analysis of the causes and characteristics of periods of high disruption-rates, which are associated with adverse surgical outcomes. MATERIALS AND METHODS: read-tv is a graphical application, and the main component of a package of the same name. read-tv generates and evaluates code to filter and visualize data. Users can view the visualization code from within the application, which facilitates reproducibility. The data input requirements are simple, a table with a time column with no missing values. The input can either be in the form of a file, or an in-memory dataframe– which is effective for rapid visualization during curation. RESULTS: We used read-tv to automatically detect surgical disruption cascades. We found that the most common disruption type during a cascade was training, followed by equipment. DISCUSSION: read-tv fills a need for visualization software of surgical disruptions and other longitudinal data. Every visualization is reproducible, the exact source code that read-tv executes to create a visualization is available from within the application. read-tv is generalizable, it can plot any tabular dataset given the simple requirements that there is a numeric, datetime, or datetime string column with no missing values. Finally, the tab-based architecture of read-tv is easily extensible, it is relatively simple to add new functionality by implementing a tab in the source code. CONCLUSION: read-tv enables quick identification of patterns through customizable longitudinal plots; faceting; CPA; and user-specified filters. The package is available on GitHub under an MIT license.
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spelling pubmed-79356102021-03-10 Research and Exploratory Analysis Driven—Time-data Visualization (read-tv) software Del Gaizo, John Catchpole, Ken R Alekseyenko, Alexander V JAMIA Open Application Notes MOTIVATION: Research & Exploratory Analysis Driven Time-data Visualization (read-tv) is an open source R Shiny application for visualizing irregularly and regularly spaced longitudinal data. read-tv provides unique filtering and changepoint analysis (CPA) features. The need for these analyses was motivated by research of surgical work-flow disruptions in operating room settings. Specifically, for the analysis of the causes and characteristics of periods of high disruption-rates, which are associated with adverse surgical outcomes. MATERIALS AND METHODS: read-tv is a graphical application, and the main component of a package of the same name. read-tv generates and evaluates code to filter and visualize data. Users can view the visualization code from within the application, which facilitates reproducibility. The data input requirements are simple, a table with a time column with no missing values. The input can either be in the form of a file, or an in-memory dataframe– which is effective for rapid visualization during curation. RESULTS: We used read-tv to automatically detect surgical disruption cascades. We found that the most common disruption type during a cascade was training, followed by equipment. DISCUSSION: read-tv fills a need for visualization software of surgical disruptions and other longitudinal data. Every visualization is reproducible, the exact source code that read-tv executes to create a visualization is available from within the application. read-tv is generalizable, it can plot any tabular dataset given the simple requirements that there is a numeric, datetime, or datetime string column with no missing values. Finally, the tab-based architecture of read-tv is easily extensible, it is relatively simple to add new functionality by implementing a tab in the source code. CONCLUSION: read-tv enables quick identification of patterns through customizable longitudinal plots; faceting; CPA; and user-specified filters. The package is available on GitHub under an MIT license. Oxford University Press 2021-03-01 /pmc/articles/PMC7935610/ /pubmed/33709063 http://dx.doi.org/10.1093/jamiaopen/ooab007 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Application Notes
Del Gaizo, John
Catchpole, Ken R
Alekseyenko, Alexander V
Research and Exploratory Analysis Driven—Time-data Visualization (read-tv) software
title Research and Exploratory Analysis Driven—Time-data Visualization (read-tv) software
title_full Research and Exploratory Analysis Driven—Time-data Visualization (read-tv) software
title_fullStr Research and Exploratory Analysis Driven—Time-data Visualization (read-tv) software
title_full_unstemmed Research and Exploratory Analysis Driven—Time-data Visualization (read-tv) software
title_short Research and Exploratory Analysis Driven—Time-data Visualization (read-tv) software
title_sort research and exploratory analysis driven—time-data visualization (read-tv) software
topic Application Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935610/
https://www.ncbi.nlm.nih.gov/pubmed/33709063
http://dx.doi.org/10.1093/jamiaopen/ooab007
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