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2162. Factors Affecting the Geographic Variability of Antibiotic-Resistant Healthcare-Associated Infections in the United States Using the CDC’s Antibiotic Resistance Patient Safety Atlas

BACKGROUND: National surveillance is proposed to be part of a National Strategy to Combat Antibiotic Resistance (AR) in the United States; recent access of state-summary metrics around antibiotic use and antibiotic resistance allows an opportunity to evaluate variability in AR among healthcare-assoc...

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Autores principales: Kubes, Julianne, Fridkin, Scott
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252951/
http://dx.doi.org/10.1093/ofid/ofy210.1818
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author Kubes, Julianne
Fridkin, Scott
author_facet Kubes, Julianne
Fridkin, Scott
author_sort Kubes, Julianne
collection PubMed
description BACKGROUND: National surveillance is proposed to be part of a National Strategy to Combat Antibiotic Resistance (AR) in the United States; recent access of state-summary metrics around antibiotic use and antibiotic resistance allows an opportunity to evaluate variability in AR among healthcare-associated infections (HAIs) between U.S. states. METHODS: We utilized data from 2016 accessible in the CDCÕs AR Patient Safety Atlas to create state-level values for the no. of HAIs (CLABSI, CAUTI, SSI) by select AR reported to NHSN, prescribing rates of outpatient antibiotics by class, and percentage of hospitals having full antibiotic stewardship programs. Other available data included 2016 CDC’s Healthcare-Associated Infections Progress Report and U.S. Census Data. We correlated (Pearson’s partial correlation coefficients) the state prevalence (% testing resistant) for multidrug-resistant P. aeruginosa (MDR-PA), extended-spectrum cephalosporin-resistant E. coli (ESC-E. coli), and methicillin-resistant S. aureus (MRSA) from HAIs with potential predictors; multivariate logistic regression was used to assess independence. RESULTS: States prevalence of HAI AR varied and was explained in part by no. of skilled nursing facility bed days for MRSA (P = 0.002), % of population black for MRSA (P < 0.001) and ESC-E. coli (P < 0.001), % of population > 65 for ESC-E. coli (P < 0.001) and MDR-PA (P < 0.001), and no. of LTACHs for MDR-PA (P = 0.01). After adjusting for these, rates of outpatient fluoroquinolone (FQ) and cephalosporin prescribing (figure) were significant predictors of ESC-R E. coli HAIs (adjusted OR 1.02, P < 0.001 and 1.01, P < 0.001, respectively) and FQ rates for MRSA HAIs (aOR 1.01, P = 0.004); the MRSA correlation was slightly elevated in states with a higher population of African-Americans. Of note, % hospitals with inpatient stewardship did not explain geographic variability in any HAI AR studied. CONCLUSION: Outpatient antibiotic prescribing rates can explain much of the state-to-state variability in studied HAI-related AR even after adjusting for differences in age and healthcare facility composition. Stewardship across the spectrum of healthcare delivery is likely needed to improve patient safety in acute care hospitals. [Image: see text] DISCLOSURES: All authors: No reported disclosures.
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spelling pubmed-62529512018-11-28 2162. Factors Affecting the Geographic Variability of Antibiotic-Resistant Healthcare-Associated Infections in the United States Using the CDC’s Antibiotic Resistance Patient Safety Atlas Kubes, Julianne Fridkin, Scott Open Forum Infect Dis Abstracts BACKGROUND: National surveillance is proposed to be part of a National Strategy to Combat Antibiotic Resistance (AR) in the United States; recent access of state-summary metrics around antibiotic use and antibiotic resistance allows an opportunity to evaluate variability in AR among healthcare-associated infections (HAIs) between U.S. states. METHODS: We utilized data from 2016 accessible in the CDCÕs AR Patient Safety Atlas to create state-level values for the no. of HAIs (CLABSI, CAUTI, SSI) by select AR reported to NHSN, prescribing rates of outpatient antibiotics by class, and percentage of hospitals having full antibiotic stewardship programs. Other available data included 2016 CDC’s Healthcare-Associated Infections Progress Report and U.S. Census Data. We correlated (Pearson’s partial correlation coefficients) the state prevalence (% testing resistant) for multidrug-resistant P. aeruginosa (MDR-PA), extended-spectrum cephalosporin-resistant E. coli (ESC-E. coli), and methicillin-resistant S. aureus (MRSA) from HAIs with potential predictors; multivariate logistic regression was used to assess independence. RESULTS: States prevalence of HAI AR varied and was explained in part by no. of skilled nursing facility bed days for MRSA (P = 0.002), % of population black for MRSA (P < 0.001) and ESC-E. coli (P < 0.001), % of population > 65 for ESC-E. coli (P < 0.001) and MDR-PA (P < 0.001), and no. of LTACHs for MDR-PA (P = 0.01). After adjusting for these, rates of outpatient fluoroquinolone (FQ) and cephalosporin prescribing (figure) were significant predictors of ESC-R E. coli HAIs (adjusted OR 1.02, P < 0.001 and 1.01, P < 0.001, respectively) and FQ rates for MRSA HAIs (aOR 1.01, P = 0.004); the MRSA correlation was slightly elevated in states with a higher population of African-Americans. Of note, % hospitals with inpatient stewardship did not explain geographic variability in any HAI AR studied. CONCLUSION: Outpatient antibiotic prescribing rates can explain much of the state-to-state variability in studied HAI-related AR even after adjusting for differences in age and healthcare facility composition. Stewardship across the spectrum of healthcare delivery is likely needed to improve patient safety in acute care hospitals. [Image: see text] DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2018-11-26 /pmc/articles/PMC6252951/ http://dx.doi.org/10.1093/ofid/ofy210.1818 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Abstracts
Kubes, Julianne
Fridkin, Scott
2162. Factors Affecting the Geographic Variability of Antibiotic-Resistant Healthcare-Associated Infections in the United States Using the CDC’s Antibiotic Resistance Patient Safety Atlas
title 2162. Factors Affecting the Geographic Variability of Antibiotic-Resistant Healthcare-Associated Infections in the United States Using the CDC’s Antibiotic Resistance Patient Safety Atlas
title_full 2162. Factors Affecting the Geographic Variability of Antibiotic-Resistant Healthcare-Associated Infections in the United States Using the CDC’s Antibiotic Resistance Patient Safety Atlas
title_fullStr 2162. Factors Affecting the Geographic Variability of Antibiotic-Resistant Healthcare-Associated Infections in the United States Using the CDC’s Antibiotic Resistance Patient Safety Atlas
title_full_unstemmed 2162. Factors Affecting the Geographic Variability of Antibiotic-Resistant Healthcare-Associated Infections in the United States Using the CDC’s Antibiotic Resistance Patient Safety Atlas
title_short 2162. Factors Affecting the Geographic Variability of Antibiotic-Resistant Healthcare-Associated Infections in the United States Using the CDC’s Antibiotic Resistance Patient Safety Atlas
title_sort 2162. factors affecting the geographic variability of antibiotic-resistant healthcare-associated infections in the united states using the cdc’s antibiotic resistance patient safety atlas
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6252951/
http://dx.doi.org/10.1093/ofid/ofy210.1818
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