Antibiogram-Derived Radial Decision Trees: An Innovative Approach to Susceptibility Data Display
Rocco J. Perla and Paul P. Belliveau
DOI : 10.3844/ajidsp.2005.124.127
American Journal of Infectious Diseases
Volume 1, Issue 2
Hospital antibiograms (ABGMs) are often presented in the form of large 2-factor (single organism vs. single antimicrobial) tables. Presenting susceptibility data in this fashion, although of value, does have limitations relative to drug resistant subpopulations. As the crisis of antimicrobial drug-resistance continues to escalate globally, clinicians need (1) to have access to susceptibility data that, for isolates resistant to first-line drugs, indicates susceptibility to second line drugs and (2) to understand the probabilities of encountering such organisms in a particular institution. This article describes a strategy used to transform data in a hospital ABGM into a probability-based radial decision tree (RDT) that can be used as a guide to empiric antimicrobial therapy. Presenting ABGM data in the form of a radial decision tree versus a table makes it easier to visually organize complex data and to demonstrate different levels of therapeutic decision-making. The RDT model discussed here may also serve as a more effective tool to understand the prevalence of different resistant subpopulations in a given institution compared to the traditional ABGM.
© 2005 Rocco J. Perla and Paul P. Belliveau. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.