CASSIA: An assistant for identifying clinically and statistically significant decreases in antimicrobial susceptibility
April 9, 2018
M. L. Tlachac, Elke Rundensteiner, Kerri Barton, Scott Troppy, Kirthana Beaulac, Shira Doron, Jian Zou,
Published in: 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI): Date of Conference: 4-7 March 2018; Date Added to IEEE Xplore: 09 April 2018. DOI: 10.1109/BHI.2018.8333450
Abstract
In this paper we introduce CASSIA, an assistant that facilitates rapid identification of antibiotic-bacteria pairs demonstrating decreases in susceptibility that need to be monitored. Specifically, CASSIA detects clinically and statistically significant decreases in susceptibility using antibiogram data. While previous studies have used the chi-squared test to evaluate the statistical significance of changes in antimicrobial susceptibility, these studies have not addressed the detection of clinical significance. CASSIA identifies statistically significant differences in susceptibility from antibiograms using chi-squared testing. CASSIA then proceeds to calculate clinical significant changes in susceptibility by propagating the maximum potential error of one report to multiple reports using the standard error formula. CASSIA is demonstrated on the Massachusetts statewide antibiogram data set. The benefits of CASSIA include immediate, consistent identification of clinically and statistically significant decreases in susceptibility without the need for an experienced domain expert.