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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: [email protected]
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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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References

Antibiotic resistance threats in the United States, 2013. Centers for Disease Control and Prevention website. http://www.cdc.gov/drugresistance/threat-report-2013. Published 2013. Accessed April 15, 2019.Google Scholar
National strategy for combating antibiotic-resistant bacteria. The White House website. https://obamawhitehouse.archives.gov/sites/default/files/docs/carb_national_strategy.pdf. Published September 2014. Accessed April 15, 2019.Google Scholar
Summary of requirements for unnecessary drugs–F329 State Operations Manual (SOM); Appendix PP; Rev 107, 04-04-2014, pp. 563–588. Centers for Medicare and Medicaid Services website. https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/downloads/som107ap_pp_guidelines_ltcf.pdf. Published 2014. Accessed April 15, 2019.Google Scholar
Summary of requirements for medication errors–F332 and 333 State Operations Manual (SOM); Appendix PP; Rev 107, 04-04-2014, pp. 430–439. Centers for Medicare and Medicaid Services website. https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/downloads/som107ap_pp_guidelines_ltcf.pdf. Published 2014. Accessed April 15, 2019.Google Scholar
Summary of requirements for drug regimen review–F428 State Operations Manual (SOM); Appendix PP; Rev 107, 04-04-2014 pp. 539–548. Centers for Medicare and Medicaid Services website. https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/downloads/som107ap_pp_guidelines_ltcf.pdf. Published 2014. Accessed April 15, 2019.Google Scholar
Core elements of hospital antibiotic stewardship programs. Centers for Disease Control and Prevention website. https://www.cdc.gov/antibiotic-use/healthcare/implementation/core-elements.html Published 2015. Accessed March 18, 2019.Google Scholar
Drinka, P, Podzorski, RP, Griffin, V, et al. Antibiogram of urinary isolates. J Am Med Dir Assoc 14: 443.CrossRefGoogle Scholar
Dellit, TH, Owens, RC, McGowan, JE Jr, et al. Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America guidelines for developing an institutional program to enhance antimicrobial stewardship. Clin Infect Dis 2007;44:159–177.CrossRefGoogle Scholar
Pakyz, AL. The utility of hospital antibiograms as tools for guiding empiric therapy and tracking resistance. Insights from the Society of Infectious Diseases Pharmacists. Pharmacotherapy 2007;27:1306–1312.CrossRefGoogle ScholarPubMed
Hindler, JF, Stelling, J. Analysis and presentation of cumulative antibiograms: a new consensus guideline from the Clinical and Laboratory Standards Institute. Clin Infect Dis 2007;44:867–873.CrossRefGoogle ScholarPubMed
Furuno, JP, Comer, AC, Johnson, JK, et al. Using antibiograms to improve antibiotic prescribing in skilled nursing facilities. Infect Control Hosp Epidemiol 2014;35 suppl 3:S56–S61.CrossRefGoogle ScholarPubMed
Moehring, RW, Hazen, KC, Hawkins, MR, Drew, RH, Sexton, DJ, Anderson, DJ. Challenges in preparation of cumulative antibiogram reports for community hospitals. J Clin Microbiol 2015;53:2977–2982.CrossRefGoogle ScholarPubMed
Nursing home compare datasets. Centers for Medicare and Medicaid Services website. https://data.medicare.gov/data/nursing-home-compare. Accessed December 20, 2017.Google Scholar
Georgia health districts. Georgia Department of Community Health website. https://dph.georgia.gov/public-health-districts. Accessed February 19, 2019.Google Scholar
Jump, RLP, Olds, DM, Seifi, N, et al. Effective antimicrobial stewardship in a long-term care facility through an infectious disease consultation service: keeping a lid on antibiotic use. Infect Control Hosp Epidemiol 2012;33:1185–1192.CrossRefGoogle Scholar
Nicolle, LE. Antimicrobial stewwardship in long-term care facilities: what is effective? Antimicrob Resist Infect Contr 2014;3:6.CrossRefGoogle ScholarPubMed
Var, SK, Hadi, R, Khardori, NM. Evaluation of regional antibiograms to monitor antimicrobial resistance in Hampton Roads, Virginia. Ann Clin Microbiol Antimicrob 2015;14:22.CrossRefGoogle ScholarPubMed
Lim, CJ, Kong, DCM, Stuart, RL. Reducing inappropriate antibiotic prescribing in the residential care setting: current perspectives. Clin Interven Aging 2014;9:165–177.Google ScholarPubMed
Delisle, G, Quach, C, Domingo, MC, et al. Escherichia coli antimicrobial susceptibility profile and cumulative antibiogram to guide empirical treatment of uncomplicated urinary tract infections in women in the province of Quebec, 2010–2015. J Antimicrob Chemother 2016;71:3562–3567.CrossRefGoogle Scholar
Slayton, RB, Toth, D, Lee, BY, et al. Vital signs: estimated effects of a coordinated approach for action to reduce antibiotic-resistant infections in health care facilities—United States. Morbid Mortal Wkly Rept 2015;64:826–831.CrossRefGoogle ScholarPubMed
State specific antibiotic resistance investments. Centers for Disease Control and Prevention website. https://www.cdc.gov/drugresistance/solutions-initiative/overview.html. Published 2017. Accessed April 15, 2019.Google Scholar
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