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Excess Length of Stay Attributable to Clostridium difficile Infection (CDI) in the Acute Care Setting: A Multistate Model

Published online by Cambridge University Press:  26 May 2015

Vanessa W. Stevens ,
Karim Khader ,
Richard E. Nelson ,
Makoto Jones ,
Michael A. Rubin ,
Kevin A. Brown ,
Martin E. Evans ,
Tom Greene ,
Eric Slade  and
Matthew H. Samore
Vanessa W. Stevens
Affiliation:
VA Salt Lake City Health Care System, Salt Lake City, Utah Pharmacotherapy Outcomes Research Center, University of Utah College of Pharmacy, Salt Lake City, Utah
Karim Khader
Affiliation:
VA Salt Lake City Health Care System, Salt Lake City, Utah Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah
Richard E. Nelson
Affiliation:
VA Salt Lake City Health Care System, Salt Lake City, Utah Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah
Makoto Jones
Affiliation:
VA Salt Lake City Health Care System, Salt Lake City, Utah Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah
Michael A. Rubin
Affiliation:
VA Salt Lake City Health Care System, Salt Lake City, Utah Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah
Kevin A. Brown
Affiliation:
VA Salt Lake City Health Care System, Salt Lake City, Utah Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah
Martin E. Evans
Affiliation:
Veterans Health Administration, Methicillin-Resistant Staphylococcus aureus/Multidrug-Resistant Organisms Prevention Office, National Infectious Diseases Service, Lexington, Kentucky
Tom Greene
Affiliation:
VA Salt Lake City Health Care System, Salt Lake City, Utah Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah
Eric Slade
Affiliation:
Mental Illness Resource Education and Clinical Center (MIRECC), VA Capitol Health Care System, Baltimore, Maryland
Matthew H. Samore
Affiliation:
VA Salt Lake City Health Care System, Salt Lake City, Utah Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah
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Abstract

BACKGROUND

Standard estimates of the impact of Clostridium difficile infections (CDI) on inpatient lengths of stay (LOS) may overstate inpatient care costs attributable to CDI. In this study, we used multistate modeling (MSM) of CDI timing to reduce bias in estimates of excess LOS.

METHODS

A retrospective cohort study of all hospitalizations at any of 120 acute care facilities within the US Department of Veterans Affairs (VA) between 2005 and 2012 was conducted. We estimated the excess LOS attributable to CDI using an MSM to address time-dependent bias. Bootstrapping was used to generate 95% confidence intervals (CI). These estimates were compared to unadjusted differences in mean LOS for hospitalizations with and without CDI.

RESULTS

During the study period, there were 3.96 million hospitalizations and 43,540 CDIs. A comparison of unadjusted means suggested an excess LOS of 14.0 days (19.4 vs 5.4 days). In contrast, the MSM estimated an attributable LOS of only 2.27 days (95% CI, 2.14–2.40). The excess LOS for mild-to-moderate CDI was 0.75 days (95% CI, 0.59–0.89), and for severe CDI, it was 4.11 days (95% CI, 3.90–4.32). Substantial variation across the Veteran Integrated Services Networks (VISN) was observed.

CONCLUSIONS

CDI significantly contributes to LOS, but the magnitude of its estimated impact is smaller when methods are used that account for the time-varying nature of infection. The greatest impact on LOS occurred among patients with severe CDI. Significant geographic variability was observed. MSM is a useful tool for obtaining more accurate estimates of the inpatient care costs of CDI.

Infect. Control Hosp. Epidemiol. 2015;36(9):1024–1030

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 36 , Issue 9 , September 2015 , pp. 1024 - 1030
Copyright
© 2015 by The Society for Healthcare Epidemiology of America. All rights reserved 

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Footnotes

PREVIOUS PRESENTATION: Selected results from this manuscript were presented in poster format at ID Week 2014 in Philadelphia, Pennsylvania, October 8–12, 2014.

The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States government.

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