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Effect of Time of Daily Data Collection on the Calculation of Catheter-associated Urinary Tract Infection Rates

INTRODUCTION: According to the National Healthcare Safety Network (NHSN) definitions for Catheter-associated urinary tract infections (CAUTI) rates, determination of the number of urinary catheter days must occur by calculating the number of catheters in place “for each day of the month, at the same...

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Autores principales: Donnelly, Lane F., Wood, Matthew, Loh, Ling, Tekic, Natasa, Shin, Andrew Y., Scheinker, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8389923/
https://www.ncbi.nlm.nih.gov/pubmed/34476317
http://dx.doi.org/10.1097/pq9.0000000000000466
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author Donnelly, Lane F.
Wood, Matthew
Loh, Ling
Tekic, Natasa
Shin, Andrew Y.
Scheinker, David
author_facet Donnelly, Lane F.
Wood, Matthew
Loh, Ling
Tekic, Natasa
Shin, Andrew Y.
Scheinker, David
author_sort Donnelly, Lane F.
collection PubMed
description INTRODUCTION: According to the National Healthcare Safety Network (NHSN) definitions for Catheter-associated urinary tract infections (CAUTI) rates, determination of the number of urinary catheter days must occur by calculating the number of catheters in place “for each day of the month, at the same time of day” but does not define at what time of day this occurs. The purpose of this review was to determine if a data collection time of 11 am would yield a greater collection of urinary catheter days than that done at midnight. METHODS: During a 20-month period, the number of urinary catheter days was calculated using once-a-day electronic measurements to identify a urinary catheter presence. We used data collected at 11 am and collected at midnight (our historic default) in comparing the calculated urinary catheter days and resultant CAUTI rates. RESULTS: There were 7,548 patients who had a urinary tract catheter. The number of urinary catheter days captured using the 11 am collection time was 15,425, and using the midnight collection time was 10,234, resulting in a 50.7% increase. The CAUTI rate per 1,000 urinary catheter days calculated using the 11 am collection method was 0.58, and using the midnight collection method was 0.88, a reduced CAUTI rate of 33.6%. CONCLUSION: The data collection time can significantly impact the calculation of urinary catheter days and on calculated CAUTI rates. Variations in how healthcare systems define their denominator per current National Healthcare Safety Network policy may result in significant differences in reported rates.
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spelling pubmed-83899232021-09-01 Effect of Time of Daily Data Collection on the Calculation of Catheter-associated Urinary Tract Infection Rates Donnelly, Lane F. Wood, Matthew Loh, Ling Tekic, Natasa Shin, Andrew Y. Scheinker, David Pediatr Qual Saf Individual QI projects from single institutions INTRODUCTION: According to the National Healthcare Safety Network (NHSN) definitions for Catheter-associated urinary tract infections (CAUTI) rates, determination of the number of urinary catheter days must occur by calculating the number of catheters in place “for each day of the month, at the same time of day” but does not define at what time of day this occurs. The purpose of this review was to determine if a data collection time of 11 am would yield a greater collection of urinary catheter days than that done at midnight. METHODS: During a 20-month period, the number of urinary catheter days was calculated using once-a-day electronic measurements to identify a urinary catheter presence. We used data collected at 11 am and collected at midnight (our historic default) in comparing the calculated urinary catheter days and resultant CAUTI rates. RESULTS: There were 7,548 patients who had a urinary tract catheter. The number of urinary catheter days captured using the 11 am collection time was 15,425, and using the midnight collection time was 10,234, resulting in a 50.7% increase. The CAUTI rate per 1,000 urinary catheter days calculated using the 11 am collection method was 0.58, and using the midnight collection method was 0.88, a reduced CAUTI rate of 33.6%. CONCLUSION: The data collection time can significantly impact the calculation of urinary catheter days and on calculated CAUTI rates. Variations in how healthcare systems define their denominator per current National Healthcare Safety Network policy may result in significant differences in reported rates. Lippincott Williams & Wilkins 2021-08-26 /pmc/articles/PMC8389923/ /pubmed/34476317 http://dx.doi.org/10.1097/pq9.0000000000000466 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Individual QI projects from single institutions
Donnelly, Lane F.
Wood, Matthew
Loh, Ling
Tekic, Natasa
Shin, Andrew Y.
Scheinker, David
Effect of Time of Daily Data Collection on the Calculation of Catheter-associated Urinary Tract Infection Rates
title Effect of Time of Daily Data Collection on the Calculation of Catheter-associated Urinary Tract Infection Rates
title_full Effect of Time of Daily Data Collection on the Calculation of Catheter-associated Urinary Tract Infection Rates
title_fullStr Effect of Time of Daily Data Collection on the Calculation of Catheter-associated Urinary Tract Infection Rates
title_full_unstemmed Effect of Time of Daily Data Collection on the Calculation of Catheter-associated Urinary Tract Infection Rates
title_short Effect of Time of Daily Data Collection on the Calculation of Catheter-associated Urinary Tract Infection Rates
title_sort effect of time of daily data collection on the calculation of catheter-associated urinary tract infection rates
topic Individual QI projects from single institutions
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8389923/
https://www.ncbi.nlm.nih.gov/pubmed/34476317
http://dx.doi.org/10.1097/pq9.0000000000000466
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