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Creating reasonable antibiograms for antibiotic stewardship programs in nursing homes: Analysis of 260 facilities in a large geographic region, 2016–2017

Published online by Cambridge University Press:  28 May 2019

Scott K. Fridkin Open the ORCID record for Scott K. Fridkin [Opens in a new window] ,
Jacob Pack ,
Giancarlo Licitra ,
Ziduo Zheng ,
Russell Watkins ,
Steve Price ,
Mayfield Camp  and
Renee Moore
Scott K. Fridkin*
Affiliation:
Department of Medicine, School of Medicine, Emory University, Atlanta, Georgia
Jacob Pack
Affiliation:
Clinical Laboratory Services, Inc., Winder, Georgia
Giancarlo Licitra
Affiliation:
Department of Medicine, School of Medicine, Emory University, Atlanta, Georgia
Ziduo Zheng
Affiliation:
Biostatistics and Bioinformatics, Emory University Rollins School of Public Health, Atlanta, Georgia
Russell Watkins
Affiliation:
Clinical Laboratory Services, Inc., Winder, Georgia
Steve Price
Affiliation:
Clinical Laboratory Services, Inc., Winder, Georgia
Mayfield Camp
Affiliation:
Clinical Laboratory Services, Inc., Winder, Georgia
Renee Moore
Affiliation:
Biostatistics and Bioinformatics, Emory University Rollins School of Public Health, Atlanta, Georgia
*
Author for correspondence: Scott K. Fridkin, Email: SFridki@emory.edu
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Abstract

Objective:

To determine the best nursing home facility characteristics for aggregating antibiotic susceptibility testing results across nursing homes to produce a useful annual antibiogram that nursing homes can use in their antimicrobial stewardship programs.

Design:

Derivation cohort study.

Setting:

Center for Medicare and Medicaid Services (CMS) certified skilled nursing facilities in Georgia (N = 231).

Participants:

All residents of eligible facilities submitting urine culture specimens for microbiologic testing at a regional referral laboratory.

Methods:

Crude and adjusted metrics of antibiotic resistance prevalence (percent of isolates testing susceptible) for 5 bacterial species commonly recovered from urine specimens were calculated using mixed linear models to determine which facility characteristics were predictive of testing antibiotic susceptibility.

Results:

In a single year, most facilities had an insufficient number of isolates tested to create facility-specific antibiograms: 49% of facilities had sufficient Escherichia coli isolates tested, but only about 1 in 10 had sufficient isolates of Klebsiella pneumoniae, Proteus mirabilis, Enterococcus faecalis, or Pseudomonas aeruginosa. After accounting for antibiotic tested and age of the patient, facility characteristics predictive of susceptibility were: E. coli, region, year, average length of stay; K. pneumoniae, region, bed size; P. mirabilis, region; and for E. faecalis or P. aerginosa no facility parameter remained in the model.

Conclusions:

Nursing homes often have insufficient data to create facility-specific antibiograms; aggregating data across nursing homes in a region is a statistically sound approach to overcoming data shortages in nursing home stewardship programs.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 40 , Issue 8 , August 2019 , pp. 839 - 846
Copyright
© 2019 by The Society for Healthcare Epidemiology of America. All rights reserved. 

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