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A dataset examining the impact of direct electronic medical record interfacing on the accuracy of point-of-care urinalysis results

Point-of-care testing is widely used in a variety of clinical settings. While this testing provides immediate and actionable clinical information, it is prone to error in both the interpretation and reporting of results. Point-of-care urinalysis presents unique opportunities for errors, ranging from...

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Autores principales: Rogers, Kai J., Krasowski, Matthew D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10014286/
https://www.ncbi.nlm.nih.gov/pubmed/36936643
http://dx.doi.org/10.1016/j.dib.2023.109012
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author Rogers, Kai J.
Krasowski, Matthew D.
author_facet Rogers, Kai J.
Krasowski, Matthew D.
author_sort Rogers, Kai J.
collection PubMed
description Point-of-care testing is widely used in a variety of clinical settings. While this testing provides immediate and actionable clinical information, it is prone to error in both the interpretation and reporting of results. Point-of-care urinalysis presents unique opportunities for errors, ranging from variation in visual interpretation to input of results. The data included here represent the results from 63,279 urinalyses from 36,780 unique patients performed over a span of three years at an academic medical center and its associated clinics. The data include the patient age/legal sex, methodology (instrument and test strip used), and the available test results (color, clarity, glucose, bilirubin, ketones, specific gravity, blood, pH, protein, urobilinogen, nitrite, and leukocyte esterase). Additionally, we include the method of interface between the testing instrumentation and our electronic medical record (EMR). These fell into one of three broad categories: “Interfaced” (results directly transmitted from the urinalysis instrument to the EMR via specialized data interface), “Manual” (results input by selecting from a drop-down menu in the laboratory information system), and “Enter/Edit” (results typed freely into a text field in the EMR). Analysis of this data was primarily a direct comparison of detectable errors (typos, uninterpretable results, and results outside the reportable range) as a function of the method of entry into the EMR. Secondary analysis comparing the impact of restricting drop-down menu options for urine color and clarity was also performed. These data are of use to others as they are diverse in terms of the test performed and the method of interface. Others may wish to analyze these data when making decisions as to how to perform and report these tests and when estimating risks of error with various methods of data entry.
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spelling pubmed-100142862023-03-16 A dataset examining the impact of direct electronic medical record interfacing on the accuracy of point-of-care urinalysis results Rogers, Kai J. Krasowski, Matthew D. Data Brief Data Article Point-of-care testing is widely used in a variety of clinical settings. While this testing provides immediate and actionable clinical information, it is prone to error in both the interpretation and reporting of results. Point-of-care urinalysis presents unique opportunities for errors, ranging from variation in visual interpretation to input of results. The data included here represent the results from 63,279 urinalyses from 36,780 unique patients performed over a span of three years at an academic medical center and its associated clinics. The data include the patient age/legal sex, methodology (instrument and test strip used), and the available test results (color, clarity, glucose, bilirubin, ketones, specific gravity, blood, pH, protein, urobilinogen, nitrite, and leukocyte esterase). Additionally, we include the method of interface between the testing instrumentation and our electronic medical record (EMR). These fell into one of three broad categories: “Interfaced” (results directly transmitted from the urinalysis instrument to the EMR via specialized data interface), “Manual” (results input by selecting from a drop-down menu in the laboratory information system), and “Enter/Edit” (results typed freely into a text field in the EMR). Analysis of this data was primarily a direct comparison of detectable errors (typos, uninterpretable results, and results outside the reportable range) as a function of the method of entry into the EMR. Secondary analysis comparing the impact of restricting drop-down menu options for urine color and clarity was also performed. These data are of use to others as they are diverse in terms of the test performed and the method of interface. Others may wish to analyze these data when making decisions as to how to perform and report these tests and when estimating risks of error with various methods of data entry. Elsevier 2023-03-01 /pmc/articles/PMC10014286/ /pubmed/36936643 http://dx.doi.org/10.1016/j.dib.2023.109012 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Rogers, Kai J.
Krasowski, Matthew D.
A dataset examining the impact of direct electronic medical record interfacing on the accuracy of point-of-care urinalysis results
title A dataset examining the impact of direct electronic medical record interfacing on the accuracy of point-of-care urinalysis results
title_full A dataset examining the impact of direct electronic medical record interfacing on the accuracy of point-of-care urinalysis results
title_fullStr A dataset examining the impact of direct electronic medical record interfacing on the accuracy of point-of-care urinalysis results
title_full_unstemmed A dataset examining the impact of direct electronic medical record interfacing on the accuracy of point-of-care urinalysis results
title_short A dataset examining the impact of direct electronic medical record interfacing on the accuracy of point-of-care urinalysis results
title_sort dataset examining the impact of direct electronic medical record interfacing on the accuracy of point-of-care urinalysis results
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10014286/
https://www.ncbi.nlm.nih.gov/pubmed/36936643
http://dx.doi.org/10.1016/j.dib.2023.109012
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