Urine cultures collected from catheterized patients have a high likelihood of false-positive results due to colonization. We examined the impact of a clinical decision support (CDS) tool that includes catheter information on test utilization and patient-level outcomes.

This before-and-after intervention study was conducted at 3 hospitals in North Carolina. In March 2021, a CDS tool was incorporated into urine-culture order entry in the electronic health record, providing education about indications for culture and suggesting catheter removal or exchange prior to specimen collection for catheters present >7 days. We used an interrupted time-series analysis with Poisson regression to evaluate the impact of CDS implementation on utilization of urinalyses and urine cultures, antibiotic use, and other outcomes during the pre- and postintervention periods.

The CDS tool was prompted in 38,361 instances of urine cultures ordered in all patients, including 2,133 catheterized patients during the postintervention study period. There was significant decrease in urine culture orders (1.4% decrease per month; P < .001) and antibiotic use for UTI indications (2.3% decrease per month; P = .006), but there was no significant decline in CAUTI rates in the postintervention period. Clinicians opted for urinary catheter removal in 183 (8.5%) instances. Evaluation of the safety reporting system revealed no apparent increase in safety events related to catheter removal or reinsertion.

CDS tools can aid in optimizing urine culture collection practices and can serve as a reminder for removal or exchange of long-term indwelling urinary catheters at the time of urine-culture collection.

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.

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.

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.