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Using macros in microsoft excel to facilitate cleaning of research data

Background: Retrospective chart review studies may be delayed by inability to export clean clinical data from an electronic medical record (EMR) or data repository. Macros are pre-programmed procedures that can be used in Microsoft Excel to help streamline the process of cleaning clinical datasets....

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Autores principales: Bauzon, Justin, Murphy, Caleb, Wahi-Gururaj, Sandhya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8462890/
https://www.ncbi.nlm.nih.gov/pubmed/34567457
http://dx.doi.org/10.1080/20009666.2021.1954282
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author Bauzon, Justin
Murphy, Caleb
Wahi-Gururaj, Sandhya
author_facet Bauzon, Justin
Murphy, Caleb
Wahi-Gururaj, Sandhya
author_sort Bauzon, Justin
collection PubMed
description Background: Retrospective chart review studies may be delayed by inability to export clean clinical data from an electronic medical record (EMR) or data repository. Macros are pre-programmed procedures that can be used in Microsoft Excel to help streamline the process of cleaning clinical datasets. Objectives: To demonstrate how macros may be useful for researchers at community hospitals and smaller academic health centers that lack informatics support. Methods: Using an intrinsic function of our institution’s EMR, vital signs and lab results from 20 individual hospitalizations were exported to a spreadsheet. Two macros were developed to sort through these datasets and output them into a specified format. The speed of macro-assisted data cleaning was compared to manual transcription. Results: Time spent on data cleaning was significantly reduced when using macro-assisted sorting compared to the manual approach for both vital signs (46.5 seconds versus 12.3 minutes per record, a 94% reduction; P < 0.001) and labs (13.7 seconds versus 2.6 minutes per record, a 91% reduction; P < 0.001). Conclusions:Macros offer a flexible and efficient tool for cleaning large sets of clinical data, particularly when an institution lacks informatics support or EMR functionality to export clinical data in an analysis-ready format.
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spelling pubmed-84628902021-09-25 Using macros in microsoft excel to facilitate cleaning of research data Bauzon, Justin Murphy, Caleb Wahi-Gururaj, Sandhya J Community Hosp Intern Med Perspect Brief Report Background: Retrospective chart review studies may be delayed by inability to export clean clinical data from an electronic medical record (EMR) or data repository. Macros are pre-programmed procedures that can be used in Microsoft Excel to help streamline the process of cleaning clinical datasets. Objectives: To demonstrate how macros may be useful for researchers at community hospitals and smaller academic health centers that lack informatics support. Methods: Using an intrinsic function of our institution’s EMR, vital signs and lab results from 20 individual hospitalizations were exported to a spreadsheet. Two macros were developed to sort through these datasets and output them into a specified format. The speed of macro-assisted data cleaning was compared to manual transcription. Results: Time spent on data cleaning was significantly reduced when using macro-assisted sorting compared to the manual approach for both vital signs (46.5 seconds versus 12.3 minutes per record, a 94% reduction; P < 0.001) and labs (13.7 seconds versus 2.6 minutes per record, a 91% reduction; P < 0.001). Conclusions:Macros offer a flexible and efficient tool for cleaning large sets of clinical data, particularly when an institution lacks informatics support or EMR functionality to export clinical data in an analysis-ready format. Taylor & Francis 2021-09-20 /pmc/articles/PMC8462890/ /pubmed/34567457 http://dx.doi.org/10.1080/20009666.2021.1954282 Text en © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of Greater Baltimore Medical Center. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Brief Report
Bauzon, Justin
Murphy, Caleb
Wahi-Gururaj, Sandhya
Using macros in microsoft excel to facilitate cleaning of research data
title Using macros in microsoft excel to facilitate cleaning of research data
title_full Using macros in microsoft excel to facilitate cleaning of research data
title_fullStr Using macros in microsoft excel to facilitate cleaning of research data
title_full_unstemmed Using macros in microsoft excel to facilitate cleaning of research data
title_short Using macros in microsoft excel to facilitate cleaning of research data
title_sort using macros in microsoft excel to facilitate cleaning of research data
topic Brief Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8462890/
https://www.ncbi.nlm.nih.gov/pubmed/34567457
http://dx.doi.org/10.1080/20009666.2021.1954282
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