Hospital-acquired Clostridioides difficile infection among patients at an urban safety-net hospital in Philadelphia: Demographics, neighborhood deprivation, and the transferability of national statistics


b>Objective:To investigate associations between healthcare-associated Clostridioides difficile infection and patient demographics at an urban safety-net hospital and compare findings with national surveillance statistics.

Methods:Study participants were selected using a case-control design using medical records collected between August 2014 and May 2018 at Hahnemann University Hospital in Philadelphia. Controls were frequency matched to cases by age and length of stay. Final sample included 170 cases and 324 controls. Neighborhood-level factors were measured using American Community Survey data. Multilevel models were used to examine infection by census tract, deprivation index, race/ethnicity, insurance type, referral location, antibiotic use, and proton-pump inhibitor use.

Results:Patients on Medicare compared to private insurance had 2.04 times (95% CI, 1.31–3.20) the odds of infection after adjusting for all covariables. Prior antibiotic use (2.70; 95% CI, 1.64–4.46) was also associated with infection, but race or ethnicity and referral location were not. A smaller proportion of hospital cases occurred among white patients (25% vs 44%) and patients over the age of 65 (39% vs 56%) than expected based on national surveillance statistics.

Conclusions:Medicare and antibiotics were associated with Clostridioides difficile infection, but evidence did not indicate association with race or ethnicity. This finding diverges from national data in that infection is higher among white people compared to nonwhite people. Furthermore, a greater proportion of hospital cases were aged <65 years than expected based on national data. National surveillance statistics on CDI may not be transportable to safety-net hospitals, which often disproportionately serve low-income, nonwhite patients.

Infection Control and Hospital Epidemiology
Daniel T. Vader
Postdoctoral Researcher