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Comparisons of antimicrobial use among hospitals are difficult to interpret owing to variations in patient case mix. Risk-adjustment strategies incorporating larger numbers of variables haves been proposed as a method to improve comparisons for antimicrobial stewardship assessments. To evaluate whether variables of varying complexity and feasibility of measurement, derived retrospectively from the electronic health records, accurately identify inpatient antimicrobial use. Retrospective cohort study, using a 2-stage random forests machine learning modeling analysis of electronic health record data. Data were split into training and testing sets to measure model performance using area under the curve and absolute error. All adult and pediatric inpatient encounters from October 1, 2015, to September 30, 2017, at 2 community hospitals and 1 academic medical center in the Duke University Health System were analyzed. A total of 204 candidate variables were categorized into 4 tiers based on feasibility of measurement from the electronic health records. Antimicrobial exposure was measured at the encounter level in 2 ways: binary (ever or never) and number of days of therapy. Analyses were stratified by age (pediatric or adult), unit type, and antibiotic group. The data set included 170 294 encounters and 204 candidate variables from 3 hospitals during the 3-year study period. Antimicrobial exposure occurred in 80 190 encounters (47%); 64 998 (38%) received 1 to 6 days of therapy, and 15 192 (9%) received 7 or more days of therapy. Two-stage models identified antimicrobial use with high fidelity (mean area under the curve, 0.85; mean absolute error, 1.0 days of therapy). Addition of more complex variables increased accuracy, with largest improvements occurring with inclusion of diagnosis information. Accuracy varied based on location and antibiotic group. Models underestimated the number of days of therapy of encounters with long lengths of stay. Models using variables derived from electronic health records identified antimicrobial exposure accurately. Future risk-adjustment strategies incorporating encounter-level information may make comparisons of antimicrobial use more meaningful for hospital antimicrobial stewardship assessments.

Mixed flora in urine cultures usually occur due to preanalytic contamination. In our outpatient urology clinic, we detected a high prevalence of mixed flora (46.2%), which was associated with female sex and older age. Patient education did not influence the rate of mixed flora. Future efforts should target high-risk patients.

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. Disclosures: None

We evaluated sampling and detection methods for fungal contamination on healthcare surface materials, comparing the efficacy of foam sponges, flocked swabs, and Replicate Organism Detection And Counting (RODAC) plates alongside culture-based quantification and quantitative polymerase chain reaction (qPCR). Findings indicate that sponge sampling and qPCR detection performed best, suggesting a foundation for future studies aiming to surveillance practices for fungi.

The origins and timing of inpatient room sink contamination with carbapenem-resistant organisms (CROs) are poorly understood. We performed a prospective observational study to describe the timing, rate, and frequency of CRO contamination of in-room handwashing sinks in 2 intensive care units (ICU) in a newly constructed hospital bed tower. Study units, A and B, were opened to patient care in succession. The patients in unit A were moved to a new unit in the same bed tower, unit B. Each unit was similarly designed with 26 rooms and in-room sinks. Microbiological samples were taken every 4 weeks from 3 locations from each study sink: the top of the bowl, the drain cover, and the p-trap. The primary outcome was sink conversion events (SCEs), defined as CRO contamination of a sink in which CRO had not previously been detected. Sink samples were obtained 22 times from September 2020 to June 2022, giving 1,638 total environmental cultures. In total, 2,814 patients were admitted to study units while sink sampling occurred. We observed 35 SCEs (73%) overall; 9 sinks (41%) in unit A became contaminated with CRO by month 10, and all 26 sinks became contaminated in unit B by month 7. Overall, 299 CRO isolates were recovered; the most common species were and . CRO contamination of sinks in 2 newly constructed ICUs was rapid and cumulative. Our findings support in-room sinks as reservoirs of CRO and emphasize the need for prevention strategies to mitigate contamination of hands and surfaces from CRO-colonized sinks.

Studies have shown that access to routine medical care is associated with the prevention, diagnosis, and treatment of chronic diseases. However, studies have not examined whether patient-reported difficulties in access to care are associated with rehospitalization in patients with cardiovascular disease. Electronic medical records and a standardized survey were used to examine cardiovascular patients admitted to a large medical center from January 1, 2015 through January 10, 2017 (n=520). All-cause readmission within 30 days of discharge was the primary outcome for analysis. Logistic regression models were used to examine the association between access to care and 30-day readmission while adjusting for patient demographics, socioeconomic status, healthcare utilization, and health status. Nearly 1-in-6 patients (15.7%) reported difficulty in accessing routine medical care; and those who were younger, male, non-white, uninsured, with heart failure, and had low social support were significantly more likely to report difficulty. Patients who reported difficulty in accessing care had significantly higher rates of 30-day readmission than patients who did not report difficulty (33.3% vs. 17.9%; P=.001); and the risks remained largely unchanged after accounting for nearly two dozen covariates (unadjusted odds ratio [OR]=2.29; 95% CI, 1.46-3.60 vs. adjusted OR=2.17; 95% CI, 1.29-3.66). Risks for readmission were especially high for patients who reported issues with transportation (OR=3.24; 95% CI, 1.28-8.16) and scheduling appointments (OR=3.56; 95% CI, 1.43-8.84), but not for other reasons (OR=1.47; 95% CI, 0.61-3.54). Cardiovascular patients who reported difficulty in accessing routine care had substantial risks of readmission within 30 days after discharge. These findings have important implications for identifying high-risk patients and developing interventions to improve access to routine medical care.

Elective surgical patients routinely bathe with chlorhexidine gluconate (CHG) at home days prior to their procedures. However, the impact of home CHG bathing on surgical site CHG concentration is unclear. We examined 3 different methods of applying CHG and hypothesized that different application methods would impact resulting CHG skin concentration.

Objectives. To examine the leadership attributes and collaborative connections of local actors from the health sector and those outside the health sector in a major place-based health initiative. Methods. We used survey data from 340 individuals in 4 Healthy Places North Carolina counties from 2014 to assess the leadership attributes (awareness, attitudes, and capacity) and network connections of local actors by their organizational sector. Results. Respondents’ leadership attributes—scored on 5-point Likert scales—were similar across Healthy Places North Carolina counties. Although local actors reported high levels of awareness and collaboration around community health improvement, we found lower levels of capacity for connecting diversity, identifying barriers, and using resources in new ways to improve community health. Actors outside the health sector had generally lower levels of capacity than actors in the health sector. Those in the health sector exhibited the majority of network ties in their community; however, they were also the most segregated from actors in other sectors. Conclusions. More capacity building around strategic action—particularly in nonhealth sectors—is needed to support efforts in making widespread changes to community health.

To assess whether measurement and feedback of chlorhexidine gluconate (CHG) skin concentrations can improve CHG bathing practice across multiple intensive care units (ICUs). A before-and-after quality improvement study measuring patient CHG skin concentrations during 6 point-prevalence surveys (3 surveys each during baseline and intervention periods). The study was conducted across 7 geographically diverse ICUs with routine CHG bathing. Adult patients in the medical ICU. CHG skin concentrations were measured at the neck, axilla, and inguinal region using a semiquantitative colorimetric assay. Aggregate unit-level CHG skin concentration measurements from the baseline period and each intervention period survey were reported back to ICU leadership, which then used routine education and quality improvement activities to improve CHG bathing practice. We used multilevel linear models to assess the impact of intervention on CHG skin concentrations. We enrolled 681 (93%) of 736 eligible patients; 92% received a CHG bath prior to survey. At baseline, CHG skin concentrations were lowest on the neck, compared to axillary or inguinal regions ( < .001). CHG was not detected on 33% of necks, 19% of axillae, and 18% of inguinal regions ( < .001 for differences in body sites). During the intervention period, ICUs that used CHG-impregnated cloths had a 3-fold increase in patient CHG skin concentrations as compared to baseline ( < .001). Routine CHG bathing performance in the ICU varied across multiple hospitals. Measurement and feedback of CHG skin concentrations can be an important tool to improve CHG bathing practice.