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Electronically Available Comorbid Conditions for Risk Prediction of Healthcare-Associated Clostridium difficile Infection

Published online by Cambridge University Press:  05 February 2018

Anthony D. Harris ,
Alyssa N. Sbarra ,
Surbhi Leekha ,
Sarah S. Jackson ,
J. Kristie Johnson ,
Lisa Pineles  and
Kerri A. Thom
Anthony D. Harris
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Alyssa N. Sbarra
Affiliation:
Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut
Surbhi Leekha
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Sarah S. Jackson
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
J. Kristie Johnson
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland Department of Pathology, University of Maryland School of Medicine, Baltimore, Maryland
Lisa Pineles
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
Kerri A. Thom*
Affiliation:
Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland
*
Address correspondence to Kerri A. Thom, MD, MPH, 655 W Baltimore Street, Bressler Hall M-021, Baltimore, MD 21201 ([email protected]).
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Abstract

OBJECTIVE

To analyze whether electronically available comorbid conditions are risk factors for Centers for Disease Control and Prevention (CDC)-defined, hospital-onset Clostridium difficile infection (CDI) after controlling for antibiotic and gastric acid suppression therapy use.

PATIENTS

Patients aged ≥18 years admitted to the University of Maryland Medical Center between November 7, 2015, and May 31, 2017.

METHODS

Comorbid conditions were assessed using the Elixhauser comorbidity index. The Elixhauser comorbidity index and the comorbid condition components were calculated using the International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM) codes extracted from electronic medical records. Bivariate associations between CDI and potential covariates for multivariable regression, including antibiotic use, gastric acid suppression therapy use, as well as comorbid conditions, were estimated using log binomial multivariable regression.

RESULTS

After controlling for antibiotic use, age, proton-pump inhibitor use, and histamine-blocker use, the Elixhauser comorbidity index was a significant risk factor for predicting CDI. There was an increased risk of 1.26 (95% CI, 1.19–1.32) of having CDI for each additional Elixhauser point added to the total Elixhauser score.

CONCLUSIONS

An increase in Elixhauser score is associated with CDI. Our study and other studies have shown that comorbid conditions are important risk factors for CDI. Electronically available comorbid conditions and scores like the Elixhauser index should be considered for risk-adjustment of CDC CDI rates.

Infect Control Hosp Epidemiol 2018;39:297–301

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 39 , Issue 3 , March 2018 , pp. 297 - 301
Copyright
© 2018 by The Society for Healthcare Epidemiology of America. All rights reserved 

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