**Background: ** Cost estimates for *Clostridium difficile* infections (CDIs) vary widely. The
costs attributable to a hospital associated CDI depend primarily on how CDI
increases a patient's length of stay (LOS). Estimating the effect of CDI on LOS
is complicated by the relationship between CDI and LOS: longer LOS increases
exposure to *C. difficile,* and *C. difficile* exposure may increase LOS via
CDI. The purpose of this study is to determine how sensitive the estimates
of the effect of CDI on LOS are to different statistical methods: how much of
the variation in cost estimates for CDI is attributable to the statistical
method used?

**Methods: ** Using data from the 2009
HCUP Nationwide Inpatient Sample (NIS), we estimate the effect of CDI on LOS
with each of the following methods: unmatched case control study (CCS), matched
CCS, propensity score matched CCS, multivariate OLS regression, propensity
score adjusted OLS, and gamma and Poisson based GLM regressions. Next, we
perform Monte Carlo simulations to estimate the accuracy of each method: we
analyze the ability of each method to recover the "true" LOS using 1200
different randomly generated sets of data based on the NIS.

**Results: ** We find the average number of days added to LOS from CDI
varied from 1.76 (SE .006) for GLM-Poisson regression to 8.20 (SE .029) for
unmatched CCS. LOS estimates are shown in Figure 1. All estimates are
statistically significant (P<.0001).

Our simulations show that the following methods tended to overestimate the effect of CDI on LOS by: 42.03% (SE .064) for unmatched CCS, 33.33% (SE .08) for matched CCS, 32.02% (SE .075) for propensity score matched CCS, 16.48% (SE .065) for OLS regression, and 16.14% (SE .065) for propensity score corrected OLS. The following methods were found to underestimate the effect of CDI on LOS by: 17.3% (SE .03) for GLM-gamma and 33.54% (SE .06) for GLM-Poisson. These estimated errors are depicted in Figure 2.

We estimate that the true effect of CDI on LOS lies somewhere between the propensity score corrected OLS estimate of 4.53 days and the GLM-gamma estimate of 1.99 days.

**Conclusion: ** Estimates of how CDI
affects LOS vary widely by the statistical method chosen. The confidence
intervals for LOS estimates using different methods did not always overlap,
i.e. some methods did not capture the true effect. Our results have broad
implications for future CDI cost studies.

**Disclosures:**

**A. Miller**,
None

**L. Polgreen**, None

**P. M. Polgreen**, None

See more of: Oral Abstract Session