ABSTRACT
Background. Inequities in healthcare among racial and ethnic minorities are globally recognized. The focus has centered on access to healthcare, equitable treatment, and optimizing outcomes. However, there has been relatively little investigation into potential racial and ethnic disparities in HAI. Methods. We performed a retrospective cohort analysis of select HAI prospectively-collected by a network of community hospitals in the southeastern US, including central line-associated bloodstream infection (CLABSI), catheterassociated urinary tract infection (CAUTI), and laboratory-identified Clostridioides difficile infection (CDI). Outcomes were stratified by race/ethnicity as captured in the electronic medical record. We defined the pre-pandemic period from 1/1/2019 to 2/29/2020 and the pandemic period from 3/1/2020 to 6/30/2021. Outcomes were reported by race/ethnicity as a proportion of the total events. Relative rates were compared using Poisson regression. Results. Overall, relatively few facilities consistently collect race/ethnicity information in surveillance databases within this hospital network (< 40%). Among 21 reporting hospitals, a greater proportion of CLABSI occurred in Black patients relative toWhite patients in both study periods (pre-pandemic, 49% vs 38%;during pandemic, 47% vs 31%;respectively, Figure 1a), while a higher proportion of CAUTI and CDI occurred in White patients (Figures 1b-c). Black patients had a 30% higher likelihood of CLABSI than White patients in the pre-COVID period (RR, 1.30;95% CI, 0.83-2.05), which was not statistically significant (Table 1). However, this risk significantly increased to 51% after the start of the pandemic (RR, 1.51;95% CI, 1.02-2.24). Similar trends were not observed in other HAI (Tables 2-3). Conclusion. We found differences in HAI rates by race/ethnicity in a network of community hospitals. Black patients had higher likelihood of CLABSI, and this likelihood increased during the pandemic. Patient safety events, including HAI, may differ across racial and ethnic groups and negatively impact health outcomes. (Figure Presented).
ABSTRACT
Background. Hospital-onset bloodstream infection (HOBSI) incidence has been proposed as a complementary quality metric to central line-associated bloodstream infection (CLABSI) surveillance. Several recent studies have detailed increases in median HOBSI and CLABSI rates during the COVID-19 pandemic. We sought to understand trends in HOBSI and CLABSI rates at a single health system in the context of COVID-19. Methods. We conducted a retrospective analysis of HOBSIs and CLABSIs at a three-hospital health system from 2017 to 2021 (Figure 1). We compared counts, denominators, and demographic data for HOBSIs and CLABSIs between the prepandemic (1/1/2017-3/30/2020) and pandemic period (4/1/2020-12/31/2021) (Table 1). We applied Poisson or negative binomial regression models to estimate the monthly change in incidence of HO-BSI and CLABSI rates over the study period. Figure 1: Definitions applied for hospital-onset bloodstream infections (HO-BSIs) and central line-associated bloodstream infections (CLABSIs). Potentially contaminated blood cultures were identified by microbiology laboratory technicians as any set of blood culture in which a single bottle was positive for organisms typically considered as skin contaminants. Uncertain cases undergo secondary review by senior lab technicians. Table 1: Count, denominator, and device utilization ratio data for hospital-onset bloodstream infections (HO-BSIs) and central line-associated bloodstream infections (CLABSIs) Note that central line utilization increased upon regression analysis (p<0.001). Results. The median monthly HOBSI rate per 1,000 patient days increased from 1.0 in the pre-pandemic to 1.3 (p< 0.01) in the pandemic period, whereas the median monthly CLABSI rate per central line days was stable (1.01 to 0.88;p=0.1;Table 2). Our regression analysis found that monthly rates of HO-BSIs increased throughout the study, but the increase was not associated with the onset of the COVID-19 pandemic based on comparisons of model fit (Figure 2;Table 3). Despite an increase in central line utilization, regression modelling found no changes in monthly CLABSIs rates with respect to time and the COVID-19 pandemic. Incidence of HOBSIs and CLABSIs by common nosocomial organisms generally increased over this time period, though time to infection onset remained unchanged in our studied population (Table 2). Conclusion. HOBSIs rates did not correlate with CLABSI incidence across a three-hospital health system from 2017 and 2021, as rates of HOBSI increased but CLABSI rates remained flat. Our observed increase in HOBSI rates did not correlate with the onset of the COVID-19 pandemic, and caution should be used in modeling the effects of COVID-19 without time-trended analysis. Further evaluation is needed to understand the etiology, epidemiology, and preventability of HO-BSI.
ABSTRACT
Background. COVID-19 shifted antibiotic stewardship program resources and changed antibiotic use (AU). Shifts in patient populations with COVID surges, including pauses to surgical procedures, and dynamic practice changes makes temporal associations difficult to interpret. Our analysis aimed to address the impact of COVID on AU after adjusting for other practice shifts. Methods. We performed a longitudinal analysis of AU data from 30 Southeast US hospitals. Three pandemic phases (1: 3/20-6/20;2: 7/20-10/20;3: 11/20-2/21) were compared to baseline (1/2018-1/2020). AU (days of therapy (DOT)/1000 patient days (PD)) was collected for all antimicrobial agents and specific subgroups: broad spectrum (NHSN group for hospital-onset infections), CAP (ceftriaxone, azithromycin, levofloxacin, moxifloxacin, and doxycycline), and antifungal. Monthly COVID burden was defined as all PD attributed to a COVID admission. We fit negative binomial GEE models to AU including phase and interaction terms between COVID burden and phase to test the hypothesis that AU changes during the phases were related to COVID burden. Models included adjustment for Charlson comorbidity, surgical volume, time since 12/2017 and seasonality. Results. Observed AU rates by subgroup varied over time;peaks were observed for different subgroups during distinct pandemic phases (Figure). Compared to baseline, we observed a significant increase in overall, broad spectrum, and CAP groups during phase 1 (Table). In phase 2, overall and CAP AU was significantly higher than baseline, but in phase 3, AU was similar to baseline. These phase changes were separate from effects of COVID burden, except in phase 1 where we observed significant effects on antifungal (increased) and CAP (decreased) AU (Table). Conclusion. Changes in hospital AU observed during early phases of the COVID pandemic appeared unrelated to COVID burden and may have been due to indirect pandemic effects (e.g., case mix, healthcare resource shifts). By pandemic phase 3, these disruptive effects were not as apparent, potentially related to shifts in non-COVID patient populations or ASP resources, availability of COVID treatments, or increased learning, diagnostic certainty, and provider comfort with avoiding antibacterials in patients with suspected COVID over time. (Figure Presented).