Abstract
BACKGROUND Reported per-patient costs of Clostridium difficile infection (CDI) vary by 2 orders of magnitude among different hospitals, implying that infection control officers need precise, local analyses to guide rational decision making between interventions. OBJECTIVE We sought to comprehensively estimate changes in length of stay (LOS) attributable to CDI at a single urban tertiary-care facility using only data automatically extractable from the electronic medical record (EMR). METHODS We performed a retrospective cohort study of 171,938 visits spanning a 7-year period. In total, 23,968 variables were extracted from EMR data recorded within 24 hours of admission to train elastic-net regularized logistic regression models for propensity score matching. To address time-dependent bias (reverse causation), we separately stratified comparisons by time of infection, and we fit multistate models. RESULTS The estimated difference in median LOS for propensity-matched cohorts varied from 3.1 days (95% CI, 2.2-3.9) to 10.1 days (95% CI, 7.3-12.2) depending on the case definition; however, dependency of the estimate on time to infection was observed. Stratification by time to first positive toxin assay, excluding probable community-acquired infections, showed a minimum excess LOS of 3.1 days (95% CI, 1.7-4.4). Under the same case definition, the multistate model averaged an excess LOS of 3.3 days (95% CI, 2.6-4.0). CONCLUSIONS In this study, 2 independent time-to-infection adjusted methods converged on similar excess LOS estimates. Changes in LOS can be extrapolated to marginal dollar costs by multiplying by average costs of an inpatient day. Infection control officers can leverage automatically extractable EMR data to estimate costs of CDI at their own institutions. Infect Control Hosp Epidemiol. 2017;38:1478-1486.
Highlights
To ensure maximally robust results and to allow comparison with prior studies, we repeated our analysis for 5 definitions of Clostridium difficile infection (CDI): Definition 1: An “008.45” ICD-9 visit diagnosis code Definition 2: ≥1 positive stool toxin enzyme immunoassay (EIA) lab result Definition 3: ≥1 positive stool toxin polymerase chain reaction (PCR) lab result Definition 4: Definition 2 or definition 3 Definition 5: Definition 1, 2, or 3 Our study period included both a period during which the EIA assay was the standard hospital laboratory test (~3 years) followed by a period during which the PCR assay was standard (~4 years)
Data were collected on demographics, length of stay (LOS), time of death, admission sources, reported medications, and the presence of a “008.45” International Classification of Disease, Ninth Revision (ICD-9) principal or secondary visit diagnosis code denoting “Intestinal infection due to Clostridium difficile.”
The differences in the median LOS, by case definition, were definition 1, 3.1 days (95% confidence interval [CI], 2.2–3.9); definition 2, 10.1 days; definition 3, 6.6 days; table 1
Summary
Prior studies vary on the use of ICD-9 discharge codes versus positive laboratory tests to define CDI cases[5,6] and identify differing positive predictive values for immunoassay and nucleic acid–based laboratory tests.[25,26,27] To ensure maximally robust results and to allow comparison with prior studies, we repeated our analysis for 5 definitions of CDI: Definition 1: An “008.45” ICD-9 visit diagnosis code Definition 2: ≥1 positive stool toxin enzyme immunoassay (EIA) lab result Definition 3: ≥1 positive stool toxin polymerase chain reaction (PCR) lab result Definition 4: Definition 2 or definition 3 Definition 5: Definition 1, 2, or 3 Our study period included both a period during which the EIA assay was the standard hospital laboratory test (~3 years) followed by a period during which the PCR assay was standard (~4 years). The hospital laboratory protocol requires unformed stool samples for either toxin assay
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