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Association between prevalence of laboratory-identified Clostridioides difficile infection (CDI) and antibiotic treatment for CDI in US acute-care hospitals, 2019

Published online by Cambridge University Press:  24 January 2022

Kerui Xu*
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia
Hsiu Wu*
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
Qunna Li
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
Jonathan R. Edwards
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
Erin N. O’Leary
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
Denise Leaptrot
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
Andrea L. Benin
Affiliation:
Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
*
Author for correspondence: Kerui Xu, E-mail: kerui.xu@fda.hhs.gov. Or Hsiu Wu, E-mail: xdh6@cdc.gov.
Author for correspondence: Kerui Xu, E-mail: kerui.xu@fda.hhs.gov. Or Hsiu Wu, E-mail: xdh6@cdc.gov.

Abstract

Objective:

To evaluate hospital-level variation in using first-line antibiotics for Clostridioides difficile infection (CDI) based on the burden of laboratory-identified (LabID) CDI.

Methods:

Using data on hospital-level LabID CDI events and antimicrobial use (AU) for CDI (oral/rectal vancomycin or fidaxomicin) submitted to the National Healthcare Safety Network in 2019, we assessed the association between hospital-level CDI prevalence (per 100 patient admissions) and rate of CDI AU (days of therapy per 1,000 days present) to generate a predicted value of AU based on CDI prevalence and CDI test type using negative binomial regression. The ratio of the observed to predicted AU was then used to identify hospitals with extreme discordance between CDI prevalence and CDI AU, defined as hospitals with a ratio outside of the intervigintile range.

Results:

Among 963 acute-care hospitals, rate of CDI prevalence demonstrated a positive dose–response relationship with rate of CDI AU. Compared with hospitals without extreme discordance (n = 902), hospitals with lower-than-expected CDI AU (n = 31) had, on average, fewer beds (median, 106 vs 208), shorter length of stay (median, 3.8 vs 4.2 days), and higher proportion of undergraduate or nonteaching medical school affiliation (48% vs 39%). Hospitals with higher-than-expected CDI AU (n = 30) were similar overall to hospitals without extreme discordance.

Conclusions:

The prevalence rate of LabID CDI had a significant dose–response association with first-line antibiotics for treating CDI. We identified hospitals with extreme discordance between CDI prevalence and CDI AU, highlighting potential opportunities for data validation and improvements in diagnostic and treatment practices for CDI.

Type
Original Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

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Footnotes

PREVIOUS PRESENTATION. A preliminary report of this research was presented at IDWeek, October 21–25, 2020. Philadelphia, Pennsylvania.

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