Hostname: page-component-745bb68f8f-f46jp Total loading time: 0 Render date: 2025-01-29T11:00:07.890Z Has data issue: false hasContentIssue false
  • English
  • Français

Demonstration of the Weighted-Incidence Syndromic Combination Antibiogram: An Empiric Prescribing Decision Aid

Published online by Cambridge University Press:  02 January 2015

Courtney Hebert ,
Jessica Ridgway ,
Benjamin Vekhter ,
Eric C. Brown ,
Stephen G. Weber  and
Ari Robicsek
Courtney Hebert*
Affiliation:
Department of Biomedical Informatics, Ohio State University, Columbus, Ohio
Jessica Ridgway
Affiliation:
University of Chicago Medical Center, Chicago, Illinois
Benjamin Vekhter
Affiliation:
Center for Health and the Social Sciences and Pritzker School of Medicine, University of Chicago, Chicago, Illinois
Eric C. Brown
Affiliation:
Center for Clinical and Research Informatics, NorthShore University HealthSystem, Evanston, Illinois
Stephen G. Weber
Affiliation:
University of Chicago Medical Center, Chicago, Illinois Center for Health and the Social Sciences and Pritzker School of Medicine, University of Chicago, Chicago, Illinois
Ari Robicsek
Affiliation:
Center for Health and the Social Sciences and Pritzker School of Medicine, University of Chicago, Chicago, Illinois Center for Clinical and Research Informatics, NorthShore University HealthSystem, Evanston, Illinois Department of Medicine and Department of Health Information Technology, NorthShore University HealthSystem, Evanston, Illinois
*
3190 Graves Hall, 333 West 10th Avenue, Columbus, OH 43210 (, [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective.

Healthcare providers need a better empiric antibiotic prescribing aid than the traditional antibiogram, which supplies no information on the relative frequency of organisms recovered in a given infection and which is uninformative in situations where multiple antimicrobials are used or multiple organisms are anticipated. We aimed to develop and demonstrate a novel empiric prescribing decision aid.

Design/Setting.

This is a demonstration involving more than 9,000 unique encounters for abdominal-biliary infection (ABI) and urinary tract infection (UTI) to a large healthcare system with a fully integrated electronic health record (EHR).

Methods.

We developed a novel method of displaying microbiology data called the weighted-incidence syndromic combination antibiogram (WISCA) for 2 clinical syndromes, ABI and UTI. The WISCA combines simple diagnosis and microbiology data from the EHR to (1) classify patients by syndrome and (2) determine, for each patient with a given syndrome, whether a given regimen (1 or more agents) would have covered all the organisms recovered for their infection. This allows data to be presented such that clinicians can see the probability that a particular regimen will cover a particular infection rather than the probability that a single drug will cover a single organism.

Results.

There were 997 encounters for ABI and 8,232 for UTI. A WISCA was created for each syndrome and compared with a traditional antibiogram for the same period.

Conclusions.

Novel approaches to data compilation and display can overcome limitations to the utility of the traditional antibiogram in helping providers choose empiric antibiotics.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 33 , Issue 4: Special Topic Issue: Antimicrobial Stewardship , April 2012 , pp. 381 - 388
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2012

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.)

References

1. Lee, S, Kim, Y, Chung, DR. Impact of discordant empirical therapy on outcome of community-acquired bacteremic acute pyelonephritis. J Infect 2011;62:159–164.Google Scholar
2. Micek, ST, Welch, EC, Khan, J, et al. Resistance to empiric antimicrobial treatment predicts outcome in severe sepsis associated with gram-negative bacteremia. J Hosp Med 2011;6:405–410.Google Scholar
3. Zilberberg, MD, Shorr, AF, Micek, ST, et al. Hospitalizations with heathcare-associated complicated skin and skin structure infections: impact of inappropriate empiric therapy on outcomes. J Hosp Med 2010;5:535–540.Google Scholar
4. Paul, M, Shani, V, Muchtar, E, Kariv, G, Robenshtok, E, Leibovici, L. Systematic review and meta-analysis of the efficacy of appropriate empiric antibiotic therapy for sepsis. Antitnicrob Agents Chemother 2010;54:4851–4863.CrossRefGoogle ScholarPubMed
5. Fridkin, SK, Edwards, JR, Courval, JM, et al. The effect of vancomycin and third-generation cephalosporins on prevalence of vancomycin-resistant enterococci in 126 U.S. adult intensive care units. Ann Intern Med 2001;135:175–183.Google Scholar
6. Mauldin, PD, Salgado, CD, Hansen, IS, Surup, DT, Bosso, JA. Attributable hospital cost and length of stay associated with health care-associated infections caused by antibiotics-resistant gram-negative bacteria. Antimicrob Agents Chemother 2010;54:109–115.Google Scholar
7. Dellit, TH, Owens, RC, McGowan, JE, 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.Google Scholar
8. Christoff, J, Tolentino, J, Mawdsley, E, Matushek, S, Pitrak, D, Weber, SG. Optimizing empirical antimicrobial therapy for infection due to gram-negative pathogens in the intensive care unit: utility of a combination antibiogram. Infect Control Hosp Epidemiol 2010;31:256–261.CrossRefGoogle ScholarPubMed
9. Fox, B, Shenk, G, Peterson, D, Spiegel, C, Maki, D. Choosing more effective antimicrobial combinations for empiric antimicrobial therapy of serious gram-negative rod infections using a dual cross-table antibiogram. Am J Infect Control 2008;36:S57–S61.Google Scholar
10. Hecker, MT, Aron, DC, Patel, NP, Lehmann, MK, Donskey, CJ. Unnecessary use of antimicrobials in hospitalized patients: current patterns of misuse with an emphasis on the antianaerobic spectrum of activity. Arc Intern Med 2003;163:972–978.Google Scholar
11. Hindier, JF, Stelling, J. Analysis and presentation of cumulative antibiograms: a new consensus guideline from the Clinical and Laboratory Standards Institute. Clin In fea Dis 2007,44:867–873.CrossRefGoogle Scholar
12. Jha, AK, DesRoches, CM, Kralovec, PD, Joshi, MS. A progress report on electronic health records in U.S. Hospitals. Health Aff (Milwood) 2010;29:1951–1957.Google Scholar
13. Department of Health and Human Services. Medicare and Medicaid programs; electronic health record incentive program; proposed rule. Fed Regist 2010;75:1844–2011.Google Scholar