Background: Methicillin-resistant S. aureus (MRSA) is known to cause frequent and severe infections in community living centers, potentially resulting in significant mortality for elderly patients. More research is needed to understand how to utilize genomic and epidemiological data to understand characteristics that may lead to increased transmission. We hypothesized that combining genomic and epidemiological information to sample patients and their environments during long-term stays, we will be able to capture a diverse set of MRSA strains. Method: This work included genome sequencing of patient and environmental samples from 11 patients within the VA Ann Arbor Healthcare System from May 4, 2021- November 16, 2022. All 11 patients tested positive for MRSA during their stay (mean days = 31). Patient and environmental samples were taken throughout their stays, screened for MRSA, and whole-genome sequenced. Single nucleotide variants (SNVs) were identified by mapping reads and calling variants against strain-specific reference genomes. We used ape v5.6-2 in R v4.2.2 to analyze and infer evolution, acquisition, and transmission events based on pairwise SNV distances. Genomic clusters were determined using stats v3.6.2, with a SNV distance threshold of 20. Result: Samples that were collected from patient bodily sites were able to reveal 20 distinct genomic clusters of MRSA (patient hands: n = 10, nares: n = 7, groin: n = 3). Environmental samples from patient environments also revealed distinct genomic MRSA clusters (tv remote: n = 9, toilet seat and bed rail: n = 6, table top, bed control, and call button: n = 5, bed curtain: n = 4, pulse ox = 2, cell phone, tray, pulse ox, mat, body hoist wrap, and bed: n = 1). Conclusion: The identification of various genomic clusters from patients and their environmental reservoirs suggests intrahost variation that can only be captured by using a more holistic approach of integrating epidemiology and genomic sequencing. Developing studies that incorporate genomic data, various environmental sources, and multiple isolates over time within community living centers can increase our understanding of strains that are more likely to transmit, survive on living and non-living surfaces and therefore lead to improved recommendation for infection prevention interventions and drivers of endemicity.

Disclosure: Lona Mody: NIH, VA, CDC, Kahn Foundation; Honoraria: UpToDate; Contracted Research: Nano-Vibronix

Asymptomatic screening for SARS-CoV-2 is recommended in healthcare settings during periods of increased incidence, yet studies in rehabilitation settings are lacking. Routine weekly post-admission asymptomatic testing in a rehabilitation facility offered marginal gain beyond syndromic and targeted unit testing and was not associated with a reduced risk of healthcare-associated COVID-19.

Background: Adult rates of non-COVID-19-related healthcare-associated infection (HAI) initially decreased and subsequently increased during the COVID-19 pandemic. Little is known about pediatric HAI rates during this period. Methods: A retrospective review of HAIs was conducted for patients admitted to the intensive care unit (PICU) at a pediatric tertiary care hospital between January 1, 2019 and November 30, 2023. Patients who spent ≥48 hours in the PICU were included. Surgical site infections were excluded. Data were obtained from infection surveillance reports; each HAI was reviewed for validity and attribution based on National Healthcare Safety Network definitions. HAIs were grouped into 3 time periods: pre-pandemic (January 2019-February 2020), pandemic (March 2020- February 2022), and post-pandemic (March 2022-November 2023). Infection rate ratios were calculated for pre-pandemic and post-pandemic periods. Results: Among 2,959 PICU patients admitted during the study period, there were 60 HAI events (4.78 per 1,000 patient days). Rates generally remained steady throughout with slight increases and decreases between time periods (Table 1). There was no significant difference in CAUTI, CLABSI, or HAVRI rates noted in the PICU between pre-pandemic and post-pandemic periods despite a significantly higher device utilization ratio in the post-pandemic period for both urinary catheters and central lines (IRR, 0.89; p < 0 .05; 95% CI, 0.82-0.97). The most frequent HAI in all time periods was CAUTI. Conclusion: Unlike reports from adult centers, no significant variation between time periods was noted for HAIs in our pediatric center. Despite numerous COVID-19-related changes in infection prevention and control measures and contexts throughout the study period, HAI rates remained stable. This may be due in part to the lower burden of critically ill COVID-19 pediatric patients compared to adult populations. Additionally, this could indicate resiliency and consistency in practice among pediatric providers throughout the pandemic. Further evaluation of pediatric HAIs in the context of the COVID-19 pandemic may reveal practices that could be replicated elsewhere to control HAI rates.

Background: During 2021–2023, an increase in Klebsiella pneumoniae carbapenemase producing Enterobacterales species (KPC-CRE) cases occurred among patients admitted to several overlapping healthcare facilities, prompting an investigation by the Colorado Department of Public Health and Environment (CDPHE). We applied social network analysis (SNA) to identify KPC-CRE networks and other multidrug-resistant organism (MDRO) transmission, created a tool for public health prevention planning and for facilities to examine their own patient transfer connectivity, and explored additional public health and emergency preparedness applications. Methods: A statewide patient transfer network was created using 2021–2022 Medicare beneficiary data. Sub-networks were isolated from the larger network to examine a cluster of facilities involved in a KPC-CRE outbreak, defined as ≥2 KPC-CRE cases related by whole genome sequencing (WGS). WGS was conducted at the CDPHE State Lab. Highly connected facilities were determined by patient transfers between at least two KPC-CRE testing facilities. Individual patient journeys were constructed using admissions and culture date. SNA was conducted in RStudio; visualizations, network metric calculations, and clustering analysis were conducted using Gephi and ArcGIS software. Results: SNA yielded 4,864 direct patient transfers between 326 healthcare facilities (220 skilled nursing facilities, 50 acute care hospitals, 32 critical access hospitals, six long term acute care hospitals, and 18 facilities not previously classified; Figure 1). WGS identified five separate KPC-CRE outbreaks among 14 patients during February 2022–January 2023; 14 patient specimens were collected at four testing facilities. We identified five highly connected facilities in addition to the four testing facilities. Patient journeys allowed us to identify possible locations of KPC-CRE transmission in four of the five outbreaks (Figure 2). CDPHE provided guidance to all involved facilities on admission screening, routine point prevalence surveys, and interfacility communication as part of an MDRO prevention plan. CDPHE then developed the transfer network into an interactive ArcGIS dashboard enabling facilities to examine their own patient transfer patterns. Conclusions: SNA enabled CDPHE to identify at-risk facilities for KPC-CRE transmission and create an interactive tool for facility and public health use. Future applications of patient transfer networks can include geographical grouping of facilities based on transfers to zone healthcare coalitions and conduct preparedness activities, and creating medical operations preparedness plans for emergencies or disasters.

Background: Health equity is a critical consideration in public health research, emphasizing the importance of fair and just access to healthcare resources. This study explores the impact of health equity factors on the incidence rates of Central Line-Associated Bloodstream Infections (CLABSI) and Methicillin-Resistant Staphylococcus aureus (MRSA) across diverse healthcare facilities in Louisiana. Methods: We conducted a comprehensive analysis utilizing 2022 data from the National Healthcare Safety Network (NHSN). Fourteen healthcare facilities were randomly selected from nine regions in Louisiana, with guidance from the 2022 NHSN external validation toolkit. Key health equity factors from Health Resources and Service Administration (HRSA) were assessed, including urbanicity, MUA/P, and HPSA_Primary Care. Risk ratios were calculated to quantify the association between these health equity factors and the incidence rates of CLABSI and MRSA. Results: The findings reveal intriguing insights into the relationship between health equity factors and infection rates. In urban settings, the risk of CLABSI was lower (Risk Ratio: 0.634, 95% CI: 0.2442–1.646), contrasting with a significantly higher risk of MRSA (Risk Ratio: 1.7, 95% CI: 1.119–2.582). This suggests a complex interplay between urbanicity and the specific infection types. For MUA/P, no significant impact on CLABSI rates was observed (Risk Ratio: 0.963, 95% CI: 0.4225–2.195), but an increased risk of MRSA emerged (Risk Ratio: 1.652, 95% CI: 1.029–2.652). In healthcare professional shortage areas for primary care (HPSA_Primary Care), both CLABSI (Risk Ratio: 1.37, 95% CI: 0.5854–3.204) and MRSA (Risk Ratio: 2.098, 95% CI: 1.305–3.372) exhibited elevated risks, though only MRSA risk was statistically significant. Conclusions: This research underscores the nuanced relationship between health equity factors and infection rates in healthcare facilities. Urban settings may contribute to a lower risk of CLABSI but a higher risk of MRSA, emphasizing the need for tailored preventive strategies. Living in medically underserved areas appears to heighten the risk of MRSA, warranting targeted interventions. Additionally, healthcare professional shortage areas for primary care demonstrate potential associations with increased risks for both CLABSI and MRSA. These findings provide valuable insights for public health practitioners, policymakers, and healthcare administrators aiming to address health disparities and enhance infection control measures in diverse healthcare settings. Further research is encouraged to unravel the multifaceted dynamics influencing infection rates and to inform targeted interventions for improved health outcomes.

We describe our experience with intravenous amoxicillin-clavulanate, which is new to the Canadian market. The majority of patients were successfully de-escalated from piperacillin-tazobactam or a carbapenem for respiratory infections or skin and soft tissue infections. Intravenous amoxicillin-clavulanate provides a good alternative in an era of rising Pseudomonas aeruginosa resistance.

Objectives The selection and dosing of surgical antimicrobial prophylaxis (SAP) to prevent surgical site infections (SSIs) is often improvisational and inappropriate in clinical settings resulting in increased risk of SSI. We therefore developed and implemented a novel computer decision support tool, OPTIMIS PRO (OPTIMIzing PROphylaxis), to improve appropriate SAP selection specific to each patient’s procedure and clinical context. Methods: This quality improvement study was conducted at a tertiary hospital network over 2 years, divided into pre-intervention (June 2021-June 2022) and post-intervention (June 2022-June 2023) periods. The intervention was a computer decision support tool programmed within the hospital’s health information system to provide patient-specific SAP recommendations based on four variables: procedure name, patient’s beta-lactam allergy status, MRSA status, and weight. Approximately 3046 unique surgical procedures were identified and a specific best practice SAP recommendation for each surgery was identified based on international practice guidelines, up-to-date literature, and panel expertise input from 14 surgical divisions at our institution. Safety of cefazolin prophylaxis among patients with self-reported beta-lactam allergy was established in the pre-operative clinic using a validated simple two-item questionnaire (Figure 1). During each standard preoperative preparation, a best practice SAP recommendation alert was then provided to the responsible anesthesiologist based on the inputs from the four aforementioned variables (Figure 2). To assess the impact of the OPTIMIS PRO tool on antibiotic prescribing, we retrospectively audited SAP selection before and after implementation, also assessing appropriateness for each of the specific inputs using evidence-based criteria. Results: Over 30 000 OPTIMIS PRO recommendation alerts were logged in the 12-month post-intervention period. A random sample audit of 408 surgical encounters were selected from the pre- and post-intervention period for analysis. Overall, appropriate antibiotic administration rose from 77% (161/208) to 92.5% (185/200) (x2=18.0, p < 0 .001) post-intervention. Usage of cefazolin among patients reporting a beta lactam allergy rose from 48% (16/33) to 100% (12/12). None of these 12 patients experienced adverse reactions as a result of beta lactam exposure. Appropriate antibiotic selection based on MRSA status was high pre- and post-implementation (98.4% vs 99.4%); but significant improvements were made for procedure-specific antibiotic selection (80.5 vs 94.5%; x2=19.3, p < 0 .001) and weight-based dosing (92.5% vs 98.4%; x2=7.45, p=0.006). Conclusion: In this first-ever intervention designed to direct SAP prescribing based on patient specific variables, we significantly improved appropriate SAP selection across a comprehensive list of surgical procedures. Future analysis should include assessing potential reductions in SSIs as result of using the support

In a national survey of lead infection preventionists in Thai hospitals, spiritual and religious importance were associated with increased odds of career satisfaction. Cultivating environments for spiritual, religious, and self-care practices within the clinical setting may help facilitate emotional well-being—and prevent burnout—among Thai healthcare workers.

Background: Inappropriate antibiotic prescribing contributes to antimicrobial resistance, a global health threat. Prior studies have used ICD-9-CM codes to estimate inappropriate prescribing rates in ambulatory settings, including emergency departments (EDs), though the last national estimates date back to 2010-2015 (Hersh et al, CID 2021). Using the most recent publicly available data, we estimated inappropriate antibiotic prescribing rates in EDs across all conditions. For further characterization, we estimated rates of inappropriate antibiotic prescribing with and without codes that could be plausible indications for which antibiotics are prescribed. Methods: We analyzed 2016-2021 data from the National Hospital Ambulatory Medical Care Survey, a nationally representative survey of EDs, subsetting to visits with ≥1 oral antibiotic prescription. Using ICD-10-CM codes (Chua et al, BMJ 2019), we calculated proportions of visits with inappropriate antibiotic prescribing; inappropriate antibiotic prescribing and ≥1 plausible antibiotic-inappropriate indication (e.g., viral infection); and inappropriate prescribing without plausible antibiotic-inappropriate indications. Among visits with plausible antibiotic-inappropriate indications, we subcategorized these further (e.g. viral infection, ophthalmologic conditions). Among visits without plausible antibiotic-inappropriate indications, we determined the most common diagnosis codes. We conducted analyses overall and separately among children (0-17 years), adults (18-64 years), and older adults (≥65 years). Results: Demographic characteristics by age group are shown in Table 1. Antibiotic prescription rates overall and for children, adults, and older adults were 18.6%, 17.8%, 19.1%, and 18.0%, respectively. Inappropriate prescription rates were 27.6%, 23.7%, 29.8%, and 24.6%, respectively. Inappropriate antibiotic prescription rates with plausible indications were 14.9%, 16.7%, 15.0%, and 12.6%, while inappropriate antibiotic prescription rates without plausible indications were 12.7%, 7.0%, 14.9%, and 12.0%, respectively (Figure 1). Rates of subcategories of inappropriate prescribing with plausible antibiotic indications overall and by age group are shown in Figure 2, with the most common diagnoses for potential signs and symptoms of infection in Table 2. The most common diagnoses for inappropriate prescribing without plausible indications are in Table 3. Conclusions: Inappropriate antibiotic prescriptions in EDs are common with a substantial proportion without plausible conditions. Most inappropriate prescriptions with plausible antibiotic-inappropriate indications are associated with potential signs and symptoms of infection without a more definitive diagnosis code, suggesting either diagnostic uncertainty or poor coding quality. Future work should distinguish between these two possibilities to determine whether stewardship efforts should focus on educational strategies to avoid unnecessary empiric antibiotic prescribing in the setting of diagnostic uncertainty, improving coding quality, or both.

Overuse of peripherally inserted central catheters (PICCs) can lead to idle central line (CL) days and increased risk for CL-associated bloodstream infections (CLABSIs). We established a midline prioritization initiative at a safety-net community hospital. This initiative led to possible CLABSI avoidance and a decline in PICC use.

Background: The number of advanced practice providers (APPs)—nurse practitioners (NPs) and physician assistants (PAs)—continues to expand across the United States. Several studies suggest differences in antibiotic prescribing rates and appropriateness by APPs compared to physicians. The objective of this analysis is to characterize population- and provider-specific outpatient antibiotic prescribing rates among physicians and APPs nationally, by state, and within urban versus rural counties. Methods: We estimated outpatient oral antibiotic prescription rates for 2011 and 2022 using county-level prescription dispensing data from IQVIA Xponent® (numerator) and population census estimates (denominator). Provider specialty denominators were provided by IQVIA, based on data from the American Medical Association. Counties were classified as urban or rural per the 2013 National Center for Health Statistics classification. National and state-level prescription volume, rates per 1000 population, and average number of prescriptions per provider were calculated for physicians, NPs, and PAs. We assessed the degree to which provider-specific rates explained the variance of the overall rate by state, using the coefficient of determination (r2) from Pearson’s correlation. Results: Between 2011 and 2022, overall U.S. antibiotic prescribing declined from 877 to 709 per 1000 population, a 19.2% relative reduction. The provider-specific proportion of the overall prescribing rate relatively decreased by 32% for physicians but increased by 157% for APPs (NPs 229%, PAs 86%; Figure 1). State-level antibiotic prescribing rates varied by provider type for both years, shifting towards proportionally greater APP prescribing in 2022 (Figure 2). For 2011 and 2022, physician prescribing rate strongly correlated with the overall state rate (r2 = 0.83 in 2011 versus 0.80 in 2022), whereas the correlation of the NP prescribing rate increased (r2 = 0.20 in 2011 versus 0.76 in 2022). A total of 60,327 (7.2%) physicians practiced in rural settings in contrast to 42,876 (12%) NPs and 14,495 (9.4%) PAs in 2022. Providers in rural counties prescribed more antibiotics per provider on average compared to urban counties; rural physicians prescribed 57% more antibiotics per provider (207 vs 132 antibiotics per provider), rural NPs prescribed 115% more (284 vs 132), and rural PAs prescribed 53% more (289 vs 189). Conclusions: The relative contribution of APPs to outpatient antibiotic prescriptions more than doubled over the past decade, accounting for 1 in 3 prescriptions in 2022. This contribution was especially prominent among NPs in rural counties. Further evaluation of antibiotic prescribing appropriateness among APPs and integration of APPs into antibiotic stewardship efforts in various settings.

Background: Approximately 40% of all antibiotics related to an acute-care hospital stay are prescribed at the time of hospital discharge. However, there is no metric to compare hospitals on their antibiotic-prescribing at this transition of care. In this study, we sought to build a risk-adjusted metric for comparing hospitals on their overall post-discharge antibiotic use. Methods: This was a retrospective study across all acute-care admissions within the Veterans Health Administration during 2018-2021. For patients discharged to home or self-care, data on antibiotics administered while inpatient and those prescribed at discharge were collected. To predict post-discharge antibiotic use (days of therapy, DOT), we built a zero-inflated negative binomial model with a random intercept for each VA medical center. Data were split into training and testing sets to measure model performance and absolute error. Covariates included patient demographics, medical specialty at discharge, comorbidities, discharge diagnoses of infection, and the length of inpatient antibiotic therapy. Outliers, defined as DOT ≥ 30, were excluded, and the predicted random intercept was used to determine hospital performance. To compare hospitals with a positive versus negative random intercept in our model (i.e. higher vs. lower than expected overall post-discharge use, respectively), we calculated mean total antibiotic duration (inpatient + post-discharge) for two uncomplicated infection types: community-acquired pneumonia (CAP) and skin and soft tissue infections (SSTI). Results: 1,804,400 patients were discharged to home or self-care across 130 hospitals. The mean age was 67.8 (SD 12.9), and 93.7% were male. Antibiotics were prescribed to 41.5% while hospitalized and 19.5% at discharge. The median number of post-discharge DOT among those prescribed post-discharge antibiotics was 7 (IQR 4-12). The predictive model detected post-discharge antibiotic use with fidelity, including accurate identification of any post-discharge antibiotic exposure (area under the precision-recall curve=0.97 ) and reliable prediction of the number of post-discharge DOT in those who were exposed (mean absolute error = 1.65; Figure 1). At negative versus positive random intercept hospitals (Figure 2), antibiotic duration for CAP and SSTIs was 7.3 versus 8.1 days (p < 0 .001) and 9.4 vs. 10.2 days (p < 0 .001), respectively. Conclusion: A model using electronically available data was able to accurately predict antibiotic use prescribed at hospital discharge. Hospitals with lower than expected overall post-discharge antibiotic use also prescribed shorter courses of antibiotic therapy for uncomplicated cases of CAP and SSTI, which may reflect more robust processes at these sites to reduce antibiotic overuse at discharge.

Disclosure: Michi Goto: Contracted Research – Merck

Background: Using antibiotics without medical guidance (non-prescription use) is a potential safety threat to individual and public health. Patients' situations can impact their intentions to use non-prescription antibiotics in the future (intended use). This survey (1) explores the dimensionality of 13 predefined situations to identify ‘summary factor,’ which include conceptually similar situations that influence patients’ intended use of non-prescription antibiotics, and (2) identifies the sociodemographic predictors associated with these summary factors. Methods: A cross-sectional survey was conducted from January 2020–June 2021 in the waiting rooms of six safety-net primary care clinics and two private emergency departments. We used principal component analysis as a data reduction technique and confirmed the factor structure of the situations (identifying three situational summary factors). Multivariate linear regression identified the sociodemographic predictors (e.g., age, gender, race, education, insurance, healthcare system, language preference, birth country, and health literacy) associated with each summary factor. Results: Of the 564 patients surveyed, the majority were female (72%), Hispanic or Latinx (47%), college-educated (44%), and received public health insurance (e.g., Medicaid or County Financial Assistance) (56%). The largest proportion of patients endorsed intended non-prescription antibiotic use for situations involving high doctor visit costs (29.8%), having leftover prescription antibiotics (50.4%), and experiencing symptom relief with prior use of antibiotics (47.5%) (Figure 1). We identified three situational summary factors: (1) perceived barriers to a doctor visit and receiving a prescription (Cronbach’s alpha [α]=0.96), (2) convenience and accessibility of non-prescription antibiotics (α=0.81), and (3) previous symptom relief with antibiotics (α=0.95). After controlling for gender, race, education, insurance, language preference, birth country, and health literacy, our multivariate regression results revealed that younger patients (P < 0 .04) and patients attending the safety-net health system (P < 0 .001) had more intended use of non-prescription antibiotics for all three summary factors (Figure 2). Conclusions: Our study revealed that younger patients and individuals receiving care from the safety-net clinics had an increased risk of intended non-prescription antibiotic use across all summary factors. Future stewardship interventions should consider the types of situations that drive patients' decisions to use antibiotics without a prescription. Interventions aimed at reducing barriers to healthcare (e.g., high costs and long waits associated with doctor appointments) and educating individuals on the risks associated with inappropriate antibiotic use while providing alternative (non-antibiotic) treatment options may reduce antibiotic use and antimicrobial resistance. Acknowledgments: This work is supported by grant number R01HS026901 from AHRQ and NRSA T-32 (6T32HC10031).

Disclosure: Barbara Trautner: Stock: Abbvie--sold in December 2023; Abbott Laboratories--sold in December 2023; -Bristol Myers Squibb--sold in December 2023; Pfizer--sold in December 2023; Consultant--Phiogen—consultant. Contracted research through NIAID for STRIVE trial, currently testing Shionogi product; Contracted research--Peptilogics; Contracted research--Genentech

Background: Inappropriate antibiotic use impacts patient safety and antimicrobial resistance patterns. In 2013, general dentists in the U.S. prescribed nearly 10% of all outpatient oral antibiotics (24.5 million prescriptions). The American Dental Association (ADA) published guidelines in 2019 recommending limited antibiotic prescribing for the treatment of dental pain and swelling. We characterized dental prescribing during 2018–2022 to assess whether antibiotic use decreased after the guideline’s release. In addition, we examined access to dental care. Methods: All antibiotic prescriptions dispensed during 2018–2022 were extracted from the IQVIA Xponent database, which captured ≥92% of all U.S. outpatient prescriptions and projected to 100% coverage. Prescriptions by general dentists were compared to total outpatient oral antibiotic prescriptions and summarized by patient sex, patient age, and prescriber geographic region. Census denominators were used to calculate prescribing rates per 1,000 persons. IQVIA general dentist counts were used to calculate dentists per 100,000 persons. Results: General dentists prescribed 24.7 million antibiotic prescriptions in 2018 (75 prescriptions per 1,000 persons) compared with 25.2 million (76 prescriptions per 1,000 persons) in 2022. During 2020–2022, general dentists prescribed >10% of all outpatient antibiotic prescriptions (range 10.7%–12.1%). In each year, prescription rates were higher for females, patients > 65 years, and among prescribers in the Northeast. In 2022, there were 58 general dentists per 100,000 persons in the United States. The highest general dentist rate was in District of Columbia (100 per 100,000 persons) and the lowest rate was in Delaware (41 per 100,000 persons). Conclusions: Despite the ADA’s 2019 guidelines, prescribing by general dentists remained stable during 2018–2022. Because the total number of antibiotic prescriptions overall decreased, general dentists’ share of all outpatient antibiotic prescriptions increased to >10% in recent years. Rate variation by patient characteristics and prescriber region may reflect differences in dental disease burden or may represent unnecessary antibiotic use. Dental antibiotic stewardship is needed, including dissemination and implementation of current prescribing guidelines. Further evaluation of prescribing indications and access to dental care is needed to inform dental stewardship priorities.