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A Simulation Study to Assess Indicators of Antimicrobial Use as Predictors of Resistance: Does It Matter Which Indicator Is Used?

OBJECTIVE: Indicators of antimicrobial use have been described previously, but few studies have compared their accuracy in prediction of antimicrobial resistance in hospital settings. This study aimed to identify conditions under which significant differences would be observed in the predictive accu...

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Autores principales: Fortin, Elise, Quach, Caroline, Fontela, Patricia S., Buckeridge, David L., Platt, Robert W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4689584/
https://www.ncbi.nlm.nih.gov/pubmed/26700185
http://dx.doi.org/10.1371/journal.pone.0145761
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author Fortin, Elise
Quach, Caroline
Fontela, Patricia S.
Buckeridge, David L.
Platt, Robert W.
author_facet Fortin, Elise
Quach, Caroline
Fontela, Patricia S.
Buckeridge, David L.
Platt, Robert W.
author_sort Fortin, Elise
collection PubMed
description OBJECTIVE: Indicators of antimicrobial use have been described previously, but few studies have compared their accuracy in prediction of antimicrobial resistance in hospital settings. This study aimed to identify conditions under which significant differences would be observed in the predictive accuracy of indicators in the context of surveillance of intensive care units (ICUs). METHODS: Ten resistance / antimicrobial use combinations were studied. We used simulation to determine if Québec’s network of 81 ICUs or the National Healthcare Safety Network (NHSN) of 2952 ICUs are large enough to allow the detection of predetermined differences between the most accurate and 1) the second most accurate indicator, and 2) the least accurate indicator, in more than 80% of simulations. For each indicator, we simulated absolute errors in prediction for each ICU and each 4-week period, for surveillance lasting up to 5 years. Absolute errors were generated following a binomial distribution, using mean absolute errors (MAEs) observed in 9 ICUs as the average proportion; simulated MAEs were compared using t-tests. This was repeated 1000 times per scenario. RESULTS: When comparing the two most accurate indicators, 80% power was reached less often with the Québec network versus the NHSN (0/20 versus 2/20 scenarios, with 5 years of surveillance data), a finding reinforced when comparing the most and least accurate indicators (3/20 versus 20/20 scenarios). When simulating 1 year of data, scenarios reaching an 80% power dropped to 0/20, comparing the two most accurate indicators with the larger network, and to 1/20, comparing the most and least accurate indicators with the smaller network. CONCLUSION: Most of the time (72%), identifying an indicator of antimicrobial use predicting antimicrobial resistance with a better accuracy was not possible. The choice of an indicator for an eventual surveillance system should rely on criteria other that predictive accuracy.
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spelling pubmed-46895842015-12-31 A Simulation Study to Assess Indicators of Antimicrobial Use as Predictors of Resistance: Does It Matter Which Indicator Is Used? Fortin, Elise Quach, Caroline Fontela, Patricia S. Buckeridge, David L. Platt, Robert W. PLoS One Research Article OBJECTIVE: Indicators of antimicrobial use have been described previously, but few studies have compared their accuracy in prediction of antimicrobial resistance in hospital settings. This study aimed to identify conditions under which significant differences would be observed in the predictive accuracy of indicators in the context of surveillance of intensive care units (ICUs). METHODS: Ten resistance / antimicrobial use combinations were studied. We used simulation to determine if Québec’s network of 81 ICUs or the National Healthcare Safety Network (NHSN) of 2952 ICUs are large enough to allow the detection of predetermined differences between the most accurate and 1) the second most accurate indicator, and 2) the least accurate indicator, in more than 80% of simulations. For each indicator, we simulated absolute errors in prediction for each ICU and each 4-week period, for surveillance lasting up to 5 years. Absolute errors were generated following a binomial distribution, using mean absolute errors (MAEs) observed in 9 ICUs as the average proportion; simulated MAEs were compared using t-tests. This was repeated 1000 times per scenario. RESULTS: When comparing the two most accurate indicators, 80% power was reached less often with the Québec network versus the NHSN (0/20 versus 2/20 scenarios, with 5 years of surveillance data), a finding reinforced when comparing the most and least accurate indicators (3/20 versus 20/20 scenarios). When simulating 1 year of data, scenarios reaching an 80% power dropped to 0/20, comparing the two most accurate indicators with the larger network, and to 1/20, comparing the most and least accurate indicators with the smaller network. CONCLUSION: Most of the time (72%), identifying an indicator of antimicrobial use predicting antimicrobial resistance with a better accuracy was not possible. The choice of an indicator for an eventual surveillance system should rely on criteria other that predictive accuracy. Public Library of Science 2015-12-23 /pmc/articles/PMC4689584/ /pubmed/26700185 http://dx.doi.org/10.1371/journal.pone.0145761 Text en © 2015 Fortin et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Fortin, Elise
Quach, Caroline
Fontela, Patricia S.
Buckeridge, David L.
Platt, Robert W.
A Simulation Study to Assess Indicators of Antimicrobial Use as Predictors of Resistance: Does It Matter Which Indicator Is Used?
title A Simulation Study to Assess Indicators of Antimicrobial Use as Predictors of Resistance: Does It Matter Which Indicator Is Used?
title_full A Simulation Study to Assess Indicators of Antimicrobial Use as Predictors of Resistance: Does It Matter Which Indicator Is Used?
title_fullStr A Simulation Study to Assess Indicators of Antimicrobial Use as Predictors of Resistance: Does It Matter Which Indicator Is Used?
title_full_unstemmed A Simulation Study to Assess Indicators of Antimicrobial Use as Predictors of Resistance: Does It Matter Which Indicator Is Used?
title_short A Simulation Study to Assess Indicators of Antimicrobial Use as Predictors of Resistance: Does It Matter Which Indicator Is Used?
title_sort simulation study to assess indicators of antimicrobial use as predictors of resistance: does it matter which indicator is used?
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4689584/
https://www.ncbi.nlm.nih.gov/pubmed/26700185
http://dx.doi.org/10.1371/journal.pone.0145761
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