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

  • Vanessa W. Stevens (a1) (a2), Karim Khader (a1) (a3), Richard E. Nelson (a1) (a3), Makoto Jones (a1) (a3), Michael A. Rubin (a1) (a3), Kevin A. Brown (a1) (a3), Martin E. Evans (a4), Tom Greene (a1) (a3), Eric Slade (a5) and Matthew H. Samore (a1) (a3)...



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.


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.


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.


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


Corresponding author

Address correspondence to Vanessa Stevens, PhD, Research Assistant Professor, IDEAS 2.0 Center, VA Salt Lake City Health Care System, Pharmacotherapy Outcomes Research Center, University of Utah College of Pharmacy, Skaggs Pharmacy Research Institute, 30 S 2000 E, Room 4961, Salt Lake City, UT 84121 (


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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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