Hostname: page-component-8448b6f56d-42gr6 Total loading time: 0 Render date: 2024-04-16T18:08:52.967Z Has data issue: false hasContentIssue false
  • English
  • Français

Development of a 51-hospital Chicagoland regional antibiogram and comparison to local hospital and national surveillance data

Published online by Cambridge University Press:  04 September 2020

David A. Butler ,
Mark Biagi ,
Vikas Gupta ,
Sarah Wieczorkiewicz ,
Lisa Young ,
Ursula Patel ,
Sandy Naegele ,
Maressa Santarossa ,
Amanda Harrington  and
Mike Postelnick
...Show all authors
David A. Butler
Affiliation:
University of Illinois at Chicago, Chicago, Illinois
Mark Biagi
Affiliation:
University of Illinois at Chicago, Rockford, Illinois
Vikas Gupta
Affiliation:
Becton, Dickinson and Company, Franklin Lakes, New Jersey
Sarah Wieczorkiewicz
Affiliation:
Advocate Lutheran General Hospital, Park Ridge, Illinois
Lisa Young
Affiliation:
Jesse Brown Veterans’ Affairs Medical Center, Chicago, Illinois
Ursula Patel
Affiliation:
Edward Hines Jr Veterans’ Affairs Hospital, Hines, Illinois
Sandy Naegele
Affiliation:
Little Company of Mary Hospital, Evergreen Park, Illinois
Maressa Santarossa
Affiliation:
Loyola University Medical Center, Maywood, Illinois
Amanda Harrington
Affiliation:
Loyola University Medical Center, Maywood, Illinois
Mike Postelnick
Affiliation:
Northwestern Memorial Hospital, Chicago, Illinois
Mira Suseno
Affiliation:
NorthShore University HealthSystem, Evanston, Illinois
Alyssa Christensen
Affiliation:
OSF Healthcare System, Peoria, Illinois
Julie Giddens
Affiliation:
OSF Healthcare System, Peoria, Illinois
Tim Murrey
Affiliation:
OSF Healthcare System, Peoria, Illinois
Amy Hanson
Affiliation:
Rush University Medical Center, Chicago, Illinois
Sharon Sam
Affiliation:
Sinai Health System, Chicago, Illinois
Natasha Pettit
Affiliation:
University of Chicago Medicine, Chicago, Illinois (Present affiliations: Albany College of Pharmacy and Health Sciences, Albany, NY [D.B.]; NorthShore University HealthSystem, Evanston, IL [S.N.]; Chicago Department of Public Health, Chicago, IL [A.H.])
Larry Danziger
Affiliation:
University of Illinois at Chicago, Chicago, Illinois
Eric Wenzler*
Affiliation:
University of Illinois at Chicago, Chicago, Illinois
*
Author for correspondence: Eric Wenzler, E-mail: wenzler@uic.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

To develop a regional antibiogram within the Chicagoland metropolitan area and to compare regional susceptibilities against individual hospitals within the area and national surveillance data.

Design:

Multicenter retrospective analysis of antimicrobial susceptibility data from 2017 and comparison to local institutions and national surveillance data.

Setting and participants:

The analysis included 51 hospitals from the Chicago–Naperville–Elgin Metropolitan Statistical Area within the state of Illinois. Overall, 18 individual collaborator hospitals provided antibiograms for analysis, and data from 33 hospitals were provided in aggregate by the Becton Dickinson Insights Research Database.

Methods:

All available antibiogram data from calendar year 2017 were combined to generate the regional antibiogram. The final Chicagoland antibiogram was then compared internally to collaborators and externally to national surveillance data to assess its applicability and utility.

Results:

In total, 167,394 gram-positive, gram-negative, fungal, and mycobacterial isolates were collated to create a composite regional antibiogram. The regional data represented the local institutions well, with 96% of the collaborating institutions falling within ±2 standard deviations of the regional mean. The regional antibiogram was able to include 4–5-fold more gram-positive and -negative species with ≥30 isolates than the median reported by local institutions. Against national surveillance data, 18.6% of assessed pathogen–antibiotic combinations crossed prespecified clinical thresholds for disparity in susceptibility rates, with notable trends for resistant gram-positive and gram-negative bacteria.

Conclusions:

Developing an accurate, reliable regional antibiogram is feasible, even in one of the largest metropolitan areas in the United States. The biogram is useful in assessing susceptibilities to less commonly encountered organisms and providing clinicians a more accurate representation of local antimicrobial resistance rates compared to national surveillance databases.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 41 , Issue 12 , December 2020 , pp. 1409 - 1418
Check for updates
Copyright
© 2020 by The Society for Healthcare Epidemiology of America. All rights reserved.

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

PREVIOUS PRESENTATION: This work was presented in part as abstract no. 2816 at the 2019 ECCMID meeting on April 16, 2019, in Amsterdam, The Netherlands.

References

Clinical and Laboratory Standards Institute (CLSI). Approved guideline M39-A4. In: Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th edition. Wayne, PA: CLSI; 2014.Google Scholar
Core elements of hospital antibiotic stewardship programs. Centers for Disease Control and Prevention website. https://www.cdc.gov/antibiotic-use/core-elements/hospital.html. Published 2019. Accessed July 20, 2020.Google Scholar
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
Fuhrmeister, AS, Jones, RN. The importance of antimicrobial resistance monitoring worldwide and the origins of SENTRY antimicrobial surveillance program. Open Forum Infect Dis 2019;6:S1–S4.CrossRefGoogle ScholarPubMed
US Census Bureau. State and Metropolitan Area Data Book, 7th ed, Washington, DC: US Census Bureau; 2010.Google Scholar
American Hospital Directory website. https://www.ahd.com/state_statistics.html. Published 2018. Accessed February 19, 2020.Google Scholar
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.Google ScholarPubMed
Guarascio, AJ, Brickett, LM, Porter, TJ, Lee, ND, Gorse, EE, Covvey, JR. Development of a statewide antibiogram to assess regional trends in antibiotic-resistant ESKAPE organisms. J Pharm Pract 2019;32:19–27.CrossRefGoogle ScholarPubMed
Hostler, CJ, Moehring, RW, Ashley, ESD, et al. 2018. Feasibility and value of developing a regional antibiogram for community hospitals. Infect Control Hosp Epidemiol 39:718–722.CrossRefGoogle ScholarPubMed
Legenza, L, Barnett, S, Lacy, J, et al. Geographic mapping of Escherichia coli susceptibility to develop a novel clinical decision support tool. Antimicrob Agents Chemother 2019;60:4840–4852.Google Scholar
Quinn, J, Joseph, J, Garey, K, et al. Antimicrobial susceptibility trends in the Chicagoland area between 1994 and 2005. Abstract no. 469. Presented at IDWeek 2007, April 9–12, 2007. Baltimore, MD.Google Scholar
Ray, MJ, Lin, MY, Weinstein, RA, Trick, WE. Spread of carbapenem-resistant Enterobacteriaceae among Illinois healthcare facilities: the role of patient sharing. Clin Infect Dis 2016;63:889–893.CrossRefGoogle ScholarPubMed
Lee, BY, Bartsch, SM, Wong, KF, et al. The potential trajectory of carbapenem-resistant Enterobacteriaceae, an emerging threat to health-care facilities, and the impact of the Centers for Disease Control and Prevention toolkit. Am J Epidemiol 2016;183:471–479.CrossRefGoogle ScholarPubMed
Lee, BY, Bartsch, SM, Hayden, MK, et al. How introducing a registry with automated alerts for carbapenem-resistant Enterobacteriaceae (CRE) May Help control CRE spread in a region. Clin Infect Dis 2019. doi: 10.1093/cid/ciz300.CrossRefGoogle Scholar
Supplementary material: File

Butler et al. supplementary material

Figures S1-S3

Download Butler et al. supplementary material(File)
File 438.8 KB