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Measuring Empiric Antibiotic Spectrum Patterns Across Space and Time

Published online by Cambridge University Press:  02 November 2020

Michael Yarrington
Affiliation:
1.) Duke University Health System and 2.) Duke Center for Antimicrobial Stewardship and Infection Prevention
Rebekah Moehring
Affiliation:
1.) Duke University Health System and 2.) Duke Center for Antimicrobial Stewardship and Infection Prevention
Deverick John Anderson
Affiliation:
1.) Duke University Health System and 2.) Duke Center for Antimicrobial Stewardship and Infection Prevention
Rebekah Wrenn
Affiliation:
1.) Duke University Health System and 2.) Duke Center for Antimicrobial Stewardship and Infection Prevention
Christina Sarubbi
Affiliation:
1.) Duke University Health System and 2.) Duke Center for Antimicrobial Stewardship and Infection Prevention
Justin Spivey
Affiliation:
1.) Duke University Health System and 2.) Duke Center for Antimicrobial Stewardship and Infection Prevention
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Abstract

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Background: Quantitative evaluation of antibiotic spectrum is an important, underutilized metric in measuring antibiotic use (AU) and may assist antimicrobial stewards in identifying targets and strategy for intervention. We evaluated the spectrum of initial antibiotic choices by hospital location, day of the week, and time of day to determine whether these factors may be associated with broad-spectrum antibiotic choices. Methods: We identified all admissions with antibiotic exposure in medical and surgical wards and critical care units in a tertiary academic medical center between July 1, 2014, and July 1, 2019. The antibiotic spectrum index (ASI), proposed by Gerber et al, is a numeric score based on the number of pathogens covered by a particular agent. We defined ASI for initial antibiotic choice as follows: ASI for each unique antibiotic administered within 24 hours of the first antibiotic administration was summed and assigned to the administration time of the first dose. We categorized time into 4 distinct categories: weekday days (Monday–Friday, 7 a.m.–7 p.m.), weekday nights, weekend days, and weekend nights. Weekend time began 7 p.m. Friday and ended 7 a.m. Monday. We constructed heatmaps stratified by hospital location. Mann-Whitney U tests were applied to evaluate differences in the distributions of ASI using weekday days as a reference. Results: Data included 90,455 unique antibiotic admissions with initial antibiotic starts in medical and surgical wards and critical care units. Patterns of ASI for initial antibiotic choice varied between unit locations and time (Figs. 1 and 2). Mean and median ASIs for initial antibiotic choices were higher for medical ward and medical ICUs than for surgical wards and surgical ICUs. Initial antibiotic choices had higher ASIs during overnight hours for all units except the surgical ICU. Notable differences in ASIs were identified between weekday and weekend prescribing for surgical units, whereas medical units demonstrated less extreme differences. Conclusion: We observed a “weekend effect” across hospital units; the most extreme occurred in surgical wards. This observation may be due to differences in patient volume and rounding patterns. For example, hospitalist and critical care units have 7-day schedules, whereas surgical wards are highly influenced by operating room schedules. Antimicrobial stewardship teams may use these data to identify strategies targeting the most opportune time and place to intervene on the spectrum of initial antibiotic choice.

Funding: None

Disclosures: None

Type
Top Oral Awards
Copyright
© 2020 by The Society for Healthcare Epidemiology of America. All rights reserved.
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