Using electronic health information to risk-stratify rates of Clostridium difficile infection in US hospitals

Marya D Zilberberg, Ying P Tabak, Dawn M Sievert, Karen G Derby, Richard S Johannes, Xiaowu Sun, L Clifford McDonald
Infection Control and Hospital Epidemiology 2011, 32 (7): 649-55

BACKGROUND: Expanding hospitalized patients' risk stratification for Clostridium difficile infection (CDI) is important for improving patient safety. We applied definitions for hospital-onset (HO) and community-onset (CO) CDI to electronic data from 85 hospitals between January 2007 and June 2008 to identify factors associated with higher HO CDI rates.

METHODS: Nonrecurrent CDI cases were identified among adult (≥ 18-year-old) inpatients by a positive C. difficile toxin assay result more than 8 weeks after any previous positive result. Case categories included HO, CO-hospital associated (CO-HA), CO-indeterminate hospital association (CO-IN), and CO-non-hospital associated (CO-NHA). C. difficile testing intensity (CDTI) was defined as the total number of C. difficile tests performed, normalized to the number of patients with at least 1 C. difficile toxin test recorded. We calculated both the incidence density and the prevalence of CDI where appropriate. We fitted a multivariable Poisson model to identify factors associated with higher HO CDI rates.

RESULTS: Among 1,351,156 unique patients with 2,022,213 admissions, 9,803 cases of CDI were identified; of these, 50.6% were HO, 17.4% were CO-HA, 9.0% were CO-IN, and 23.0% were CO-NHA. The incidence density of HO was 6.3 per 10,000 patient-days. The prevalence of CO CDI on admission was, per 10,000 admissions, 8.4 for CO-HA, 4.4 for CO-IN, and 11.1 for CO-NHA. Factors associated (P < .0001) with higher HO CDI rates included older age, higher CO-NHA prevalence on admission, and increased CDTI.

CONCLUSION: Electronic health information can be leveraged to risk-stratify HO CDI rates by patient age and CO-NHA prevalence on admission. Hospitals should optimize diagnostic testing to improve patient care and measured CDI rates.

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