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To analyze Clostridioides difficile testing in 3 hospitals in central North Carolina to validate previous racial health-disparity findings.
We completed a retrospective analysis of inpatient C. difficile tests from 2015 to 2021 at 3 university-affiliated hospitals in North Carolina. We calculated the number of C. difficile tests per 1,000 patient days stratified by race: White, Black, and non-White, non-Black (NWNB). We defined a unique C. difficile test as one that occurred in an inpatient unit with a matching laboratory accession ID and on differing calendar days. Tests were evaluated overall, by hospital, by year, and by positivity rate.
In total, 35,160 C. difficile tests and 2,571,850 patient days across all 3 hospitals from 2015 to 2021 were analyzed. The median number of C. difficile tests per 1,000 patient days was 13.85 (interquartile range [IQR], 9.88–16.07). Among all C. difficile tests, 5,225 (15%) were positive. White patients were administered more C. difficile tests (14.46 per 1,000 patient days) than Black patients (12.96; P < .0001) or NWNB race patients (10.27; P < .0001). Black patients were administered more tests than NWNB patients (P < .0001). White patients tested positive at a similar rate to Black patients (15% vs 15%; P = .3655) and higher than NWNB individuals (12%; P = .0061), and Black patients tested positive at a higher rate than NWNB patients (P = .0024).
White patients received more C. difficile tests than Black and NWNB patient groups when controlling for race patient days. Future studies should control for comorbidities and investigate community onset of C. difficile by race and ethnicity.
Since the initial publication of A Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals in 2008, the prevention of healthcare-associated infections (HAIs) has continued to be a national priority. Progress in healthcare epidemiology, infection prevention, antimicrobial stewardship, and implementation science research has led to improvements in our understanding of effective strategies for HAI prevention. Despite these advances, HAIs continue to affect ∼1 of every 31 hospitalized patients,1 leading to substantial morbidity, mortality, and excess healthcare expenditures,1 and persistent gaps remain between what is recommended and what is practiced.
The widespread impact of the coronavirus disease 2019 (COVID-19) pandemic on HAI outcomes2 in acute-care hospitals has further highlighted the essential role of infection prevention programs and the critical importance of prioritizing efforts that can be sustained even in the face of resource requirements from COVID-19 and future infectious diseases crises.3
The Compendium: 2022 Updates document provides acute-care hospitals with up-to-date, practical expert guidance to assist in prioritizing and implementing HAI prevention efforts. It is the product of a highly collaborative effort led by the Society for Healthcare Epidemiology of America (SHEA), the Infectious Disease Society of America (IDSA), the Association for Professionals in Infection Control and Epidemiology (APIC), the American Hospital Association (AHA), and The Joint Commission, with major contributions from representatives of organizations and societies with content expertise, including the Centers for Disease Control and Prevention (CDC), the Pediatric Infectious Disease Society (PIDS), the Society for Critical Care Medicine (SCCM), the Society for Hospital Medicine (SHM), the Surgical Infection Society (SIS), and others.
Background: Historically, diagnosis of urinary tract infections (UTIs) has been divided into 3 categories based on symptoms and urine culture results: not UTI, asymptomatic bacteriuria (ASB), or UTI. However, some populations (eg, older adults, catheterized patients) may not present with signs or symptoms referrable to the urinary tract or have chronic lower urinary tract symptoms (LUTS), making the diagnosis of UTI challenging. We sought to understand the clinical presentation of patients who receive urine tests in a cohort of diverse hospitals. Methods: This retrospective descriptive cohort study included all adult noncatheterized inpatient and ED encounters with paired urinalysis and urine cultures (24 hours apart) from 5 community and academic hospitals in 3 states (NC, VA, GA) between January 1, 2017, and December 31, 2019. Trained abstractors collected clinical and demographic data using a 60-question REDCap survey. The study group met with multidisciplinary experts (ID, geriatrics, urology) to define the “continuum of UTI” (Table 1), which includes 2 new categories: (1) LUTS to capture patients with chronic lower urinary tract symptoms and (2) bacteriuria of unclear significance (BUS) to capture patients who do not clinically meet criteria for ASB or UTI (eg, older adults who present with delirium and bacteriuria). The newly defined categories were compared to current guideline-based categories. We further compared ASB, BUS, and UTI categories using a lower bacterial threshold of 1,000 colony-forming units. Results: In total, 220,531 encounters met study criteria. After using a random number generator and removing duplicates, 3,392 encounters were included. Based on current IDSA guidelines, the prevalence of ASB was 32.1% (n = 975), and prevalence of patients with “not UTI” was 1,614 (53%). Applying the expert panel’s new “continuum of UTI” definitions, the prevalence of “not UTI” patients decreased to 1,147 (37.7%), due to reassignment of 467 patients (15.3%)to LUTS. The prevalence of ASB decreased by 24% due to reassignment to BUS. Lowering the bacterial threshold had a slight impact on the number of definitive UTIs (14.9 vs 15.9%) (Table 1). Conclusions: Our rigorous review of laboratory and symptom data from a diverse population dataset revealed that diagnostic uncertainty exists when assessing patients with suspicion for UTI. We propose moving away from dichotomous approach of ASB versus UTI and using the “continuum of UTI” for stewardship conversations. This approach will allow us to develop nuanced deprescribing interventions for patients with LUTS or BUS (eg, watchful waiting, shorter course therapy) that account for the unique characteristics of these populations.
Background: Blood cultures are commonly ordered for patients with low risk of bacteremia. Liberal blood-culture ordering increases the risk of false-positive results, which can lead to increased length of stay, excess antibiotics, and unnecessary diagnostic procedures. We implemented a blood-culture indication algorithm with data feedback and assessed the impact on ordering volume and percent positivity. Methods: We performed a prospective cohort study from February 2022 to November 2022 using historical controls from February 2020 to January 2022. We introduced the blood-culture algorithm (Fig. 1) in 2 adult surgical intensive care units (ICUs). Clinicians reviewed charts of eligible patients with blood cultures weekly to determine whether the blood-culture algorithm was followed. They provided feedback to the unit medical directors weekly. We defined a blood-culture event as ≥1 blood culture within 24 hours. We excluded patients aged <18 years, absolute neutrophil count <500, and heart and lung transplant recipients at the time of blood-culture review. Results: In total, 7,315 blood-culture events in the preintervention group and 2,506 blood-culture events in the postintervention group met eligibility criteria. The average monthly blood-culture rate decreased from 190 blood cultures per 1,000 patient days to 142 blood cultures per 1,000 patient days (P < .01) after the algorithm was implemented. (Fig. 2) The average monthly blood-culture positivity increased from 11.7% to 14.2% (P = .13). Average monthly days of antibiotic therapy (DOT) was lower in the postintervention period than in the preintervention period (2,200 vs 1,940; P < .01). (Fig. 3) The ICU length of stay did not change before the intervention compared to after the intervention: 10 days (IQR, 5–18) versus 10 days (IQR, 5–17; P = .63). The in-hospital mortality rate was lower during the postintervention period, but the difference was not statistically significant: 9.24% versus 8.34% (P = .17). The all-cause 30-day mortality was significantly lower during the intervention period: 11.9% versus 9.7% (P < .01). The unplanned 30-day readmission percentage was significantly lower during the intervention period (10.6% vs 7.6%; P < .01). Over the 9-month intervention, we reviewed 916 blood-culture events in 452 unique patients. Overall, 74.6% of blood cultures followed the algorithm. The most common reasons overall for ordering blood cultures were severe sepsis or septic shock (37%), isolated fever and/or leukocytosis (19%), and documenting clearance of bacteremia (15%) (Table 1). The most common indications for inappropriate blood cultures were isolated fever and/or leukocytosis (53%). Conclusions: We introduced a blood-culture algorithm with data feedback in 2 surgical ICUs and observed decreases in blood-culture volume without a negative impact on ICU LOS or mortality rate.
Background: Frequently used physical therapy (PT) equipment is notably difficult to disinfect due to equipment material and shape, however, the efficacy of standard disinfection of PT equipment is poorly understood. Methods: We completed a prospective observational microbiological analysis of fomites used in adult or pediatric PT at Duke University Health System, Durham, North Carolina, from September to December 2022. Predetermined study fomites were obtained after being used during a clinical shift and standard disinfection had been completed by clinical service staff. Fomites were split into 2 halves, left and right, for sampling. Samples were taken with premoistened cellulose sponges processed using the stomacher technique and were incubated on appropriate selective and general medias. We defined antimicrobial-resistant, clinically important pathogens (AMR-CIP) as MRSA, VRE, and MDR-gram-negative isolates, and non–AMR-CIP as MSSA, VSE, and gram-negative species. Study fomites were grouped as follows: (1) pediatric pig toy, (2) walking aids (walkers or canes), (3) balls (medicine, dodge, etc), and (4) other (foam roller, sliding board, etc). Results: In total, 47 patients, 61 fomites, and 122 were analyzed. Of the study patients, 24 (51%) were female, 13 (27%) had active infections, and 15 (32%) were on contact precautions. Because fomites were split in half, patients in the left and right study arms were identical. Overall, the median total colony-forming-units (CFU) of study fomites was 1,348 (IQR, 398–2,365): 468 (IQR, 161–1,230) for the left side study arm and 540 (IQR, 102–1,221) for the right study arm (P = .45). At the sample level, 52 (43%), 15 (12%), and 37 (30%) of 122 samples harbored any CIPs, AMR CIPs, or non-AMR CIPs, respectively. At the fomite level, 27 (44%), 5 (8%), 15(25%), and 7 (11%) of 61 fomites harbored any CIPs, only AMR-CIPs, only non-AMR CIPs, or both AMR and non-AMR CIPs, respectively. Generally, therapy balls were the most contaminated study fomites (n = 2,237; IQR, 1,425–2,658), and walking aids were most frequently contaminated with any CIPs (n = 26, 72%), AMR CIPs (n = 8, 22%), and non-AMR CIPs (n = 15, 47%). Discussion: Following routine disinfection, frequently used PT equipment remained heavily contaminated and harbored AMR and non-AMR CIPs, supporting the notion that PT equipment is difficult to disinfect via standard disinfection. Additionally, left-, and right-side fomite divisions had similar pathogens, suggesting that this sampling model of intrapatient comparisons may be helpful for resolving case-mix issues in future studies. Future work should focus on PT-specific enhanced disinfection strategies to improve the disinfection of PT equipment.
Financial support: This study was funded by PURioLABS.
We calculated the attributable cost of several healthcare-associated infections in a community hospital network: central-line–associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), hospital-onset Clostridioides difficile infections (CDI-HOs) (43 hospitals); surgical site infections (SSIs) (40 hospitals). From 2016 to 2022, the total cost of CLABSIs, CAUTIs, CDI-HOs, and SSIs was $420,012,025.
We assessed Oxivir Tb wipe disinfectant residue in a controlled laboratory setting to evaluate low environmental contamination of SARS-CoV-2. Frequency of viral RNA detection was not statistically different between intervention and control arms on day 3 (P=0.14). Environmental contamination viability is low; residual disinfectant did not significantly contribute to low contamination.
The intent of this document is to highlight practical recommendations in a concise format designed to assist acute-care hospitals in implementing and prioritizing their surgical-site infection (SSI) prevention efforts. This document updates the Strategies to Prevent Surgical Site Infections in Acute Care Hospitals published in 2014.1 This expert guidance document is sponsored by the Society for Healthcare Epidemiology of America (SHEA). It is the product of a collaborative effort led by SHEA, the Infectious Diseases Society of America (IDSA), the Association for Professionals in Infection Control and Epidemiology (APIC), the American Hospital Association (AHA), and The Joint Commission, with major contributions from representatives of a number of organizations and societies with content expertise.
This retrospective review of 4-year surveillance data revealed a higher central line-associated bloodstream infection (CLABSI) rate in non-Hispanic Black patients and higher catheter-associated urinary tract infection (CAUTI) rates in Asian and non-Hispanic Black patients compared with White patients despite similar catheter utilization between the groups.
Our surveys of nurses modeled after the Capability, Opportunity, and Motivation Model of Behavior (COM-B model) revealed that opportunity and motivation factors heavily influence urine-culture practices (behavior), in addition to knowledge (capability). Understanding these barriers is a critical step towards implementing targeted interventions to improving urine-culture practices.
In total, 50 healthcare facilities completed a survey in 2021 to characterize changes in infection prevention and control and antibiotic stewardship practices. Notable findings include sustained surveillance for multidrug-resistant organisms but decreased use of human resource-intensive interventions compared to previous surveys in 2013 and 2018 conducted prior to the COVID-19 pandemic.
Clinicians and laboratories routinely use urinalysis (UA) parameters to determine whether antimicrobial treatment and/or urine cultures are needed. Yet the performance of individual UA parameters and common thresholds for action are not well defined and may vary across different patient populations.
In this retrospective cohort study, we included all encounters with UAs ordered 24 hours prior to a urine culture between 2015 and 2020 at 3 North Carolina hospitals. We evaluated the performance of relevant UA parameters as potential outcome predictors, including sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). We also combined 18 different UA criteria and used receiver operating curves to identify the 5 best-performing models for predicting significant bacteriuria (≥100,000 colony-forming units of bacteria/mL).
In 221,933 encounters during the 6-year study period, no single UA parameter had both high sensitivity and high specificity in predicting bacteriuria. Absence of leukocyte esterase and pyuria had a high NPV for significant bacteriuria. Combined UA parameters did not perform better than pyuria alone with regard to NPV. The high NPV ≥0.90 of pyuria was maintained among most patient subgroups except females aged ≥65 years and patients with indwelling catheters.
When used as a part of a diagnostic workup, UA parameters should be leveraged for their NPV instead of sensitivity. Because many laboratories and hospitals use reflex urine culture algorithms, their workflow should include clinical decision support and or education to target symptomatic patients and focus on populations where absence of pyuria has high NPV.
We compared the effectiveness of 4 sampling methods to recover Staphylococcus aureus, Klebsiella pneumoniae and Clostridioides difficile from contaminated environmental surfaces: cotton swabs, RODAC culture plates, sponge sticks with manual agitation, and sponge sticks with a stomacher. Organism type was the most important factor in bacterial recovery.
To describe the epidemiology of complex colon surgical procedures (COLO), stratified by present at time of surgery (PATOS) surgical-site infections (SSIs) and non-PATOS SSIs and their impact on the epidemiology of colon-surgery SSIs.
Retrospective cohort study.
SSI data were prospectively collected from patients undergoing colon surgical procedures (COLOs) as defined by the National Healthcare Safety Network (NHSN) at 34 community hospitals in the southeastern United States from January 2015 to June 2019. Logistic regression models identified specific characteristics of complex COLO SSIs, complex non-PATOS COLO SSIs, and complex PATOS COLO SSIs.
Over the 4.5-year study period, we identified 720 complex COLO SSIs following 28,188 COLO surgeries (prevalence rate, 2.55 per 100 procedures). Overall, 544 complex COLO SSIs (76%) were complex non-PATOS COLO SSIs (prevalence rate [PR], 1.93 per 100 procedures) and 176 (24%) complex PATOS COLO SSIs (PR, 0.62 per 100 procedures). Age >75 years and operation duration in the >75th percentile were independently associated with non-PATOS SSIs but not PATOS SSIs. Conversely, emergency surgery and hospital volume for COLO procedures were independently associated with PATOS SSIs but not non-PATOS SSIs. The proportion of polymicrobial SSIs was significantly higher for non-PATOS SSIs compared with PATOS SSIs.
Complex PATOS COLO SSIs have distinct features from complex non-PATOS COLO SSIs. Removal of PATOS COLO SSIs from public reporting allows more accurate comparisons among hospitals that perform different case mixes of colon surgeries.
To evaluate the pattern of blood-culture utilization among a cohort of 6 hospitals to identify potential opportunities for diagnostic stewardship.
We completed a retrospective analysis of blood-culture utilization during adult inpatient or emergency department (ED) encounters in 6 hospitals from May 2019 to April 2020. We investigated 2 measures of blood-culture utilization rates (BCURs): the total number of blood cultures, defined as a unique accession number per 1,000 patient days (BCX) and a new metric of blood-culture events per 1,000 patient days to account for paired culture practices. We defined a blood-culture event as an initial blood culture and all subsequent samples for culture drawn within 12 hours for patients with an inpatient or ED encounter. Cultures were evaluated by unit type, positivity and contamination rates, and other markers evaluating the quality of blood-culture collection.
In total, 111,520 blood cultures, 52,550 blood culture events, 165,456 inpatient admissions, and 568,928 patient days were analyzed. Overall, the mean BCUR was 196 blood cultures per 1,000 patient days, with 92 blood culture events per 1,000 patient days (range, 64–155 among hospitals). Furthermore, 7% of blood-culture events were single culture events, 55% began in the ED, and 77% occurred in the first 3 hospital days. Among all blood cultures, 7.7% grew a likely pathogen, 2.1% were contaminated, and 5.9% of first blood cultures were collected after the initiation of antibiotics.
Blood-culture utilization varied by hospital and was heavily influenced by ED culture volumes. Hospital comparisons of blood-culture metrics can assist in identifying opportunities to optimize blood-culture collection practices.
Sparse recent data are available on the epidemiology of surgical site infections (SSIs) in community hospitals. Our objective was to provide updated epidemiology data on complex SSIs in community hospitals and to characterize trends of SSI prevalence rates over time.
Retrospective cohort study.
SSI data were collected from patients undergoing 26 commonly performed surgical procedures at 32 community hospitals in the southeastern United States from 2013 to 2018. SSI prevalence rates were calculated for each year and were stratified by procedure and causative pathogen.
Over the 6-year study period, 3,561 complex (deep incisional or organ-space) SSIs occurred following 669,467 total surgeries (prevalence rate, 0.53 infections per 100 procedures). The overall complex SSI prevalence rate did not change significantly during the study period: 0.58 of 100 procedures in 2013 versus 0.53 of 100 procedures in 2018 (prevalence rate ratio [PRR], 0.84; 95% CI, 0.66–1.08; P = .16). Methicillin-sensitive Staphylococcus aureus (MSSA) complex SSIs (n = 480, 13.5%) were more common than complex SSIs caused by methicillin-resistant S. aureus (MRSA; n = 363, 10.2%).
The complex SSI rate did not decrease in our cohort of community hospitals from 2013 to 2018, which is a change from prior comparisons. The reason for this stagnation is unclear. Additional research is needed to determine the proportion of or remaining SSIs that are preventable and what measures would be effective to further reduce SSI rates.
Policies that promote conversion of antibiotics from intravenous to oral route administration are considered “low hanging fruit” for hospital antimicrobial stewardship programs. We developed a simple metric based on digestive days of therapy divided by total days of therapy for targeted agents and a method for hospital comparisons. External comparisons may help identify opportunities for improving prospective implementation.
The typical 5-day work week affects healthcare outcomes. Structured work hours have also been implicated in antimicrobial prescribing choice. We developed a visualization tool to aid in evaluating breadth of antibiotic use in various time (day of week and hour of day) and space (patient location) combinations.
We evaluated antibiotic administration data from a tertiary-care academic medical center between July 1, 2018, and July 1, 2020. We calculated a cumulative empiric antibiotic spectrum score by adapting a previously validated antibiotic spectrum index (ASI) and applying that score to empiric antibiotic use. We visualized these data as a heat map based on various day-of-week–time combinations and then compared the distribution of scores between weekday nights, weekend days, and weekend nights to the typical workweek hours (weekday days, weekday days) using the Mann-Whitney U nonparametric test with a Bonferroni correction.
The analysis included 76,535 antibiotic starts across 53,900 unique patient admissions over 2 years. The mean cumulative ASI was higher in all 3 night and weekend combinations (weekday nights, 7.3; weekend days, 7.6; weekend nights, 7.5) compared to the weekday daytime hours (weekday days, 7.1) and the distribution of scores was different in all groups compared to the weekday daytime reference. The cumulative ASI was also higher in intensive care units.
Empiric antibiotic prescribing patterns differed across space and time; broader antibiotic choices occurred in the intensive care units and on nights and weekends. Visualization of these patterns aids in antimicrobial prescribing pattern recognition and may assist in finding opportunities for additional antimicrobial stewardship interventions.