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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 (, courtney.hebert@osumc.edu)
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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

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