Background: Medical tape is one of the most ubiquitous resources in the hospital. Although tape is advertised by manufacturers as a single patient-use item, half-used rolls are a common sight in hospitals. Tape is often manipulated by un-sanitized and ungloved hands and comes in close contact with patient skin. Medical tape has the potential to be a source of hospital-acquired infection as it has been documented to be colonized with pathogens ranging from MRSA to Rhizopus. Despite infection risk, currently the only clinical guidelines of tape use are outlined in the Centers for Medicare & Medicaid Services guidance for Hemodialysis patients issued in 2008 that requires “tape should be dedicated to a single patient and discarded after use” as hemodialysis patients are at higher risk of infection. However, there is a lack of standards in the practice of tape use across hospital systems. Methods: To understand the current practices and beliefs of tape use at our institution, we developed a standardized survey to query individuals from various roles (RN, Physician, Patient Care Technicians, respiratory therapists, phlebotomists) across all patient care areas at a 746-bed academic, tertiary care center. Results: 52 units were surveyed, including 225 employees. Qualitative analysis revealed a wide variety of uses for medical tape for patient care, with venipuncture, securing IVs, and wound dressings being the most common. Only 1.4% of individuals reported single use of tape rolls. 54% of individuals reported tape use behaviors that carry an elevated risk for inoculation of pathogens. 70% of individuals reported that tape was discarded after the patient was discharged from their respective area. These practices did not change across procedure-heavy areas such as the Emergency Department or the Operating Rooms, in fact only 22% of individuals surveyed reported single use of tape in these areas. Beliefs about tape use varied: 95% of individuals agreed that a roll of tape could be used multiple times on a single patient, and 52% of individuals agreed that a roll of tape could be used on multiple patients. Conclusions: Tape use practices varied across hospital units, indicating the need for standardized policies for tape use and storage. Beliefs about tape not being a single-use item were consistent across the hospital and suggest that education and culture change efforts are needed to decrease the risk for hospital-acquired infections from improper medical tape use.

Significant gaps exist in representation of diverse populations in central-line assessment education and tools. We review some of these gaps and provide some real-world guidance on how to assess central line sites in patients of all skin tones.

Background: Artificial intelligence (AI) tools have demonstrated success in US medical licensing examinations; however, their utility in infection prevention and control (IPC) remains unknown. Methods: The program of hospital epidemiology handles consultation calls and records each question and answer. Using 2022 data, we selected 31 frequently asked questions. We utilized four AI tools, including Chat GPT-3.5 and 4.0, Bing AI, and OpenEvidence, to generate answers. We predefined scales (Table 1) to capture responses by three reviewers, including two hospital epidemiologists and one infection preventionist. The mean score of ≥ 3 and ≥ 4 was considered acceptable in accuracy and completeness, respectively. We reported the percentage of responses with acceptable accuracy and completeness out of assessed questions for each category. Results: Among 31 questions, 16 were associated with isolation duration, 9 with healthcare personnel (HCP) exposure, 4 with cleaning contaminated rooms, and 2 with patient exposure. Regarding accuracy, most AI tools performed worse in questions about isolation duration, ranging between 75% and 93.8%. All AI tools, except OpenEvidence, had a 100% accuracy rate for HCP and patient exposure. All AI tools had a 100% accuracy rate for contaminated room handling. The highest overall acceptable accuracy rate was observed in Chat GPT-3.5. Regarding completeness, most AI tools performed worse in questions about isolation duration, ranging between 44% and 75%. All AI tools, except OpenEvidence, had a 100% completeness rate for contaminated rooms and patient exposure. The highest overall acceptable completeness rate was observed in Bing AI (Table 2). Conclusions: All AI tools provided reasonable answers to commonly asked IPC-related questions, although, there were variations among different tools used. AI could be used to supplement the infection control program, especially if resources are limited.

Background: Chlorhexidine gluconate bathing (CHGB) prevents healthcare associated infections (HAIs). CHGB quality is rarely assessed; prior studies identified that concentrations of CHG can be suboptimal, particularly at the neck, and if rinsed after application. In the setting of increased HAI rates on 3 high-risk units, we evaluated CHG skin concentrations, comparing results to bathing documentation and patient reports as part of a quality improvement initiative. Methods: All patients admitted to 3 high-risk units were swabbed for CHG concentration testing at the neck, bilateral upper arms, and groin. Swabs were processed using a semi-quantitative colorimetric CHG assay. A threshold of 0.001875% CHG was used to determine adequacy based on prior studies. Adequacy was assessed by body site, timing of bath, and patient-reported skin care activities using Chi-square tests in SAS 9.4. Per hospital policy, all admitted patients are bathed daily with 2% CHG pre-packed wipes. Patients without a documented CHGB for the duration of the admission were excluded. Results: CHG testing was completed on 63 patients: 23 on medical ICU, 18 surgical ICU, 22 oncology ward, yielding 249 samples. Only ward patients could report the time of last CHGB, which agreed with nursing documentation for 12/21(57%) Adequacy by sample was no different across units: 59/88(67%) Oncology, 68/90(76%) MICU, 56/71(79%) SICU, p=0.2091. Site adequacy was different by site: neck 36/63(57%), left arm 49/62(79%), right arm 50/62(81%), groin 48/62(77%), p=0.0083. Samples taken from the 11 patients with > = 24 hours since last CHGB were more likely to be below threshold concentration: 19/47(40%) versus 47/202(23%) not adequate in the recent treatment grouping. Three patients reported showering soon after the CHGB and 8 patients used moisturizing lotion. The percent of samples below threshold for the showering patients (6/12, 50%) and lotion-users (11/32, 34%) were not significantly different from the non-showering or non-lotion using patient samples (p=0.0588 and 0.2800 respectively). Conclusion: In a facility with longstanding daily CHGB policies in place, 66/249 samples from 63 patients lacked adequate concentrations of CHG for optimal HAI prevention. Even in patients with recent CHGB, 23% of sites tested revealed inadequate levels of CHG, while 60% of those overdue for CHGB kept adequate concentrations. Reliable implementation strategies are required for CHGB so as to ensure maximal infection prevention impact.

Diagnostic stewardship is increasingly recognized as a powerful tool to improve patient safety. Given the close relationship between diagnostic testing and antimicrobial misuse, antimicrobial stewardship (AMS) pharmacists should be key members of the diagnostic team. Pharmacists practicing in AMS already frequently engage with clinicians to improve the diagnostic process and have many skills needed for the implementation of diagnostic stewardship initiatives. As diagnostic stewardship becomes more broadly used, all infectious disease clinicians, including pharmacists, must collaborate to optimize patient care.

Background: External comparisons of antimicrobial use (AU) may be more informative if adjusted for encounter characteristics. Optimal methods to define input variables for encounter-level risk-adjustment models of AU are not established. Methods: This retrospective analysis of electronic health record data included 50 US hospitals in 2020-2021. We used NHSN definitions for all antibacterials days of therapy (DOT), including adult and pediatric encounters with at least 1 day present in inpatient locations. We assessed 4 methods to define input variables: 1) diagnosis-related group (DRG) categories by Yu et al., 2) adjudicated Elixhauser comorbidity categories by Goodman et al., 3) all Clinical Classification Software Refined (CCSR) diagnosis and procedure categories, and 4) adjudicated CCSR categories where codes not appropriate for AU risk-adjustment were excluded by expert consensus, requiring review of 867 codes over 4 months to attain consensus. Data were split randomly, stratified by bed size as follows: 1) training dataset including two-thirds of encounters among two-thirds of hospitals; 2) internal testing set including one-third of encounters within training hospitals, and 3) external testing set including the remaining one-third of hospitals. We used a gradient-boosted machine (GBM) tree-based model and two-staged approach to first identify encounters with zero DOT, then estimate DOT among those with >0.5 probability of receiving antibiotics. Accuracy was assessed using mean absolute error (MAE) in testing datasets. Correlation plots compared model estimates and observed DOT among testing datasets. The top 20 most influential variables were defined using modeled variable importance. Results: Our datasets included 629,445 training, 314,971 internal testing, and 419,109 external testing encounters. Demographic data included 41% male, 59% non-Hispanic White, 25% non-Hispanic Black, 9% Hispanic, and 5% pediatric encounters. DRG was missing in 29% of encounters. MAE was lower in pediatrics as compared to adults, and lowest for models incorporating CCSR inputs (Figure 1). Performance in internal and external testing was similar, though Goodman/Elixhauser variable strategies were less accurate in external testing and underestimated long DOT outliers (Figure 2). Agnostic and adjudicated CCSR model estimates were highly correlated; their influential variables lists were similar (Figure 3). Conclusion: Larger numbers of CCSR diagnosis and procedure inputs improved risk-adjustment model accuracy compared with prior strategies. Variable importance and accuracy were similar for agnostic and adjudicated approaches. However, maintaining adjudications by experts would require significant time and potentially introduce personal bias. If findings are confirmed, the need for expert adjudication of input variables should be reconsidered.

Disclosure: Elizabeth Dodds Ashley: Advisor- HealthTrackRx. David J Weber: Consultant on vaccines: Pfizer; DSMB chair: GSK; Consultant on disinfection: BD, GAMA, PDI, Germitec

Background: Clinical laboratories perform antimicrobial susceptibility testing (AST) primarily by determining the minimum inhibitory concentration (MIC) for an organism–antimicrobial combination and comparing it with established breakpoints to generate interpretations. The Antimicrobial Resistance (AR) Option of CDC’s National Healthcare Safety Network (NHSN) permits hospitals to submit clinical isolate AST data, including test values and interpretations (Figure 1). The Clinical and Laboratory Standards Institute (CLSI) periodically revises breakpoints, but their adoption by clinical laboratories can be delayed, potentially affecting national AR surveillance data accuracy. Using MIC values, instead of clinical laboratory interpretations, can improve surveillance data accuracy and overcome misclassification due to delayed uptake of revised breakpoints. We evaluated the completeness and consistency of MIC data submitted to the AR Option for fluoroquinolone-resistant Escherichia coli and methicillin-resistant Staphylococcus aureus (MRSA). Methods: We included data on (1) E. coli isolates tested for ciprofloxacin or levofloxacin susceptibility and (2) S. aureus isolates tested for oxacillin or cefoxitin susceptibility in 2022 and reported by October 1, 2023. We evaluated completeness among isolates reporting a final AST interpretation as the proportion of isolates reporting both an MIC value and interpretation. We evaluated consistency using percent agreement comparing the laboratory’s MIC interpretation (classified as resistant or not resistant) with the interpretation derived by applying 2021 CLSI M100 breakpoints to the MIC values reported for the same isolate. Results: Across 974 hospitals, fluoroquinolone MICs and interpretations were reported for 172,012/393,359 E. coli isolates (43.7%), and oxacillin or cefoxitin MICs and interpretations were reported for 38,519/79,372 S. aureus isolates (48.5%). Of isolates with both MIC values and interpretations, 157,902 (91.8%) E. coli and 7,808(79.7%) S. aureus isolates had MICs that could be classified as resistant or non-resistant (i.e., intermediate or susceptible) per CLSI breakpoints (Figure 2). The remaining MICs were unclassifiable (reported as intervals spanning CLSI breakpoints, e.g., ≤1 μg/ml ciprofloxacin for E. coli). Among isolates with classifiable MICs, the agreement between the clinical laboratory and CLSI-based interpretation was 99.5% for E. coli and 99.7% for S. aureus. Conclusion: MIC values and interpretations were available for

The burden of healthcare-associated infections (HAIs) and antimicrobial resistance (AMR) is disproportionately high in low and middle-income countries. Barriers to implementing effective antimicrobial stewardship and infection prevention programs include the lack of a structural framework, consensus guidelines, educational opportunities, trained personnel, funding, and access to resources such as manpower, information technology, and diagnostics. Socioeconomic instability with supply chain interruptions, poor skilled staff retention, absence of mandates, and inadequate support to enforce existing policies further aggravates the situation. Failure to implement measures to tackle AMR and HAIs effectively will result in repercussions globally.

Background: The 2022 Special Report: COVID-19 U.S. Impact on Antimicrobial Resistance identified continued increases in the rate of extended- spectrum beta-lactamase producing (ESBL) infections in the United States from 2017 through 2020. Using similar data sources and methodology, we examined the trends of species-specific ESBL infections from 2012-2021. Methods: We identified a cohort of patients from the PINC AI and BD Research Insights databases with a clinical culture yielding a Klebsiella pneumoniae or Escherichia coli isolate with accompanying susceptibility testing. E. coli or K. pneumoniae isolates non-susceptible to ceftriaxone, cefotaxime, ceftazidime, or cefepime were considered suggestive of ESBL production. Isolates from patients with no culture yielding the same resistance phenotype of interest in the previous 14 days were counted as an incident case. Community-onset (CO) cultures were obtained ≤ day 3 of hospitalization; hospital-onset (HO) cultures were obtained ≥ day 4. We used a raking procedure to determine weights for extrapolating the number of discharges included in our sample to match the distribution of discharges, stratified by bed size, U.S. census division, urban/rural designation, and teaching status, for U.S. hospitals included in the American Hospital Association survey. We evaluated rates over time due to the changes in number of hospitalizations during the COVID-19 pandemic. Results were stratified by HO and CO, and sterile and non-sterile specimen sources. Results: In 2021, there were 48,936 ESBL K. pneumoniae and 153,112 ESBL E. coli infections among approximately 32 million discharges. Overall, most infections were CO and from non-sterile specimens. From 2012-2021, the rate of ESBL K. pneumoniae increased from 9.54 to 15.28 per 10,000 discharges. ESBL E. coli infections increased from 2012-2020 (30.18 to 51.32 per 10,000 discharges), then declined in 2021 (47.81 per 10,000 discharges) (Table 1, Figure 1). The proportion of non-sterile ESBL E. coli declined from 88% in 2012 to 83% in 2021, and the proportion of non-sterile ESBL K. pneumoniae was 85-87% over the study period (Figure 2). Conclusion: ESBL E. coli and K. pneumoniae infections increased from 2012-2021, although the CO ESBL E. coli rate decreased between 2020 and 2021. Understanding changes in culturing practices over time may provide insights into the increased proportion of ESBL E. coli from sterile sites. Additionally, further investigation into differences in organism trends, particularly in 2021, may inform prevention strategies.

Background: Cerebrospinal fluid (CSF) cultures are commonly performed to evaluate patients with suspected bacterial meningitis. These cultures, however, can take up to 72 hours, leading to delays in antibiotic de-escalation and increased antimicrobial utilization. The turnaround for the BioFire® FilmArray® Meningitis/Encephalitis(FA/ME) panel is less than an hour, which may facilitate early de-escalation. Our study aimed to assess whether the use of FA/ME panels in combination with CSF cultures could impact antimicrobial therapy compared to cultures alone in patients treated for suspected bacterial meningitis. Methods: Our retrospective study included patients from five hospitals in Texas (2017-2023) who received empiric antibiotics for suspected community-acquired meningitis and underwent a lumbar puncture within 96 hours of admission. Patients with ventricular drains, traumatic brain injury, and non-central nervous system infections were excluded. Cases comprised patients who had an FA/ME panel performed, while controls included patients without the panel. Outcomes were defined as the empiric duration of antimicrobial therapy (days) and total days of antibiotic therapy (DOT). Wilcoxon Rank Sum test and multiple linear regression models were applied to assess the relationship between the use of the FA/ME panel and study outcomes. Independent variables comprised demographics, institution type, acuity, clinical presentation, CSF values, and FA/ME panel use. Imputation was performed using multiple imputation by chained equations. Results: A total of 193 patients were included in our study. Seventy-one patients received the FA/ME panel (along with the CSF culture), while 122 patients received the CSF culture alone (controls). The median empiric duration of antibiotic therapy in the cases and controls were 1.71 days and 1.18 days, respectively (p = .160). The median DOT in the cases and controls were eight days and six days, respectively (p = .045). After adjusting for confounders, the FA/ME panel was not significantly associated with changes in the empiric duration of antibiotic therapy (B= 0.18, p = .669, Figure 1) or DOT (B= 1.28, p = .170, Figure 2).

Conclusion: Providing FA/ME panel testing without active antimicrobial stewardship interventions did not result in a change in antimicrobial prescribing patterns. The difference from prior literature could be explained by the smaller sample size, limiting the power of the study. Further prospective antimicrobial stewardship efforts should focus on training providers on interpreting FA/ME panel results and providing prospective audits and feedback.

In this single-center observational study of 118 older adults with advanced cancer who developed non-ventilator hospital-acquired pneumonia, prolonged antibiotic durations (8–14 and ≥15 vs ≤7 d) were not associated with reduced adjusted odds of 90-day all-cause readmission or death. These data may inform antimicrobial stewardship efforts in palliative care settings.

Background: Oral antimicrobial therapy for osteoarticular infections in adults is increasingly adopted; however, the preponderance of published data and experience with oral antibiotics involves agents such as fluoroquinolones, trimethoprim-sulfamethoxazole, and clindamycin. Data supporting the use of narrower-spectrum, stewardship-friendly oral antibiotics with favorable toxicities profiles (e.g. cefadroxil) are needed. Methods: We report a case series of adults who underwent surgery for monomicrobial Gram-positive osteomyelitis, native joint septic arthritis (NJSA), prosthetic joint infection (PJI), or other orthopedic hardware infection at our institution from January 2019 through January 2022 and who subsequently received at least two weeks of oral cefadroxil. We excluded patients who had polymicrobial infection or curative amputation, or who received cefadroxil only as suppressive antibiotic therapy (SAT). Our primary outcome of interest was treatment success during followup, defined as freedom from death, unplanned surgery for infection, or readmission for worsening infection. Results: We identified 22 patients who received cefadroxil for primary treatment of osteoarticular infection. The mean age was 57.6 years, mean weight 98.6 kg, 68% were male, and none had peripheral vascular disease. Infections included PJI in 12, NJSA in 8, osteomyelitis in 7, and other hardware infections in 5; some patients had multiple infectious syndromes. Methicillin-susceptible Staphylococcus aureus (MSSA) was the most common pathogen (73%), followed by streptococci (18%), other methicillin-susceptible staphylococci (14%), and Cutibacterium acnes (5%). Half of patients received 120kg who had device infections with MSSA, two of which were managed with implant retention, suggesting pharmacokinetic/pharmacodynamic factors and biofilm burden could influence treatment outcome. Limitations of this study include its small sample size, noncomparative nature, lengthy initial intravenous antibiotic durations, and limited durations of followup. These data suggest cefadroxil merits investigation for adult osteoarticular infection in larger comparative (and ideally, prospective randomized) studies.

Background: An overall decrease of prescriptions for outpatient fluoroquinolones (FQs) following the FDA’s release of boxed warnings in 2016 was shown in a previous analysis1. An additional study found that this decline held true when further broken down by specialty 2. We sought to determine which different clinician specialties in Washington State (WA) continue to prescribe FQs and if these rates are congruent with previously conducted national analyses. Methods: We conducted a comprehensive analysis of Medicare Part D data from 2021. We identified specialty types contributing the highest proportions of FQ claims from the total volume of claims in 2021. Subsequently, we calculated the average FQ claims per 1,000 Medicare Part D beneficiaries for each specialty. The analysis excluded providers with missing beneficiary data. All dosage formulations were included (i.e. topical & oral). We repeated this process for each year from 2021 to 2013 to assess changes in the average FQ prescription rate for each specialty over time. Results: Our analysis encompassed 99,250 FQ prescriptions involving 976,209 Medicare Part D beneficiaries from January 1 to December 30, 2021. Among the specialties, urologists emerged as the highest prescribers of FQs to Medicare Part D beneficiaries, closely followed by ophthalmologists and family practitioners (Table 1). Notably, 72.4% of urologists prescribed FQs, while only 12.4% of family practitioners did so in 2021. Trend analysis indicated that the average FQ claims per 1,000 beneficiaries for urologists decreased from 251 claims per 1,000 beneficiaries (SD = 177.98) in 2013 to 130 claims per 1,000 beneficiaries (SD = 122.50) in 2021 (Figure 1A). In contrast, the only specialty types that had positive trends in average FQ claims per 1,000 beneficiaries from 2013 to 2021 included ophthalmologists, optometrists, and otolaryngologists (Figure 1A). Conclusion: Throughout the years leading up to 2021, most prescriber specialties contributing high volumes of FQ claims experienced a decline in FQ prescriptions. The positive trend noted amongst ophthalmologists, optometrists, and otolaryngologists could be due to the limited ability to differentiate between oral & topical FQ formulations within the dataset. These findings underscore the importance of understanding specialist prescribing behaviors and partnering with them to formulate tailored antibiotic stewardship guidance. By doing so, we can further promote patient safety and well-being in the context of FQ usage. Public health departments can promote more holistic antibiotic stewardship interventions and better patient safety outcomes with FQs. Ambulatory Fluoroquinolone Use in the United States 2015–2019 Outpatient Fluoroquinolone Prescription Fills.

Disclosure: Erica Stohs: Contracted research - Merck; Contracted research – bioMerieux

We examined the antibiotic prescribing rate for respiratory diagnoses (AXR) before and after onset of the COVID-19 pandemic in urgent care clinics. At the onset, AXR declined substantially due to changes in case mix. Using AXR as a stewardship metric requires monitoring of changes in case mix.

Background: The BioFire FilmArray Blood Culture Identification 2 (BCID2) Panel is used to identify organisms present in positive blood cultures within hours of detection at Virginia Commonwealth University Health System (VCUHS). BCID2 is also able to detect common resistance mechanisms including CTX-M, the most common extended-spectrum beta-lactamase (ESBL) in the United States, and several carbapenemases. The Antimicrobial Stewardship Program (ASP) at VCUHS established optimal treatment recommendations for each organism identified by BCID2 based on the detection of a resistance mechanism and local resistance patterns. The recommendation for the majority of Enterobacterales without a detected resistance mechanism is ceftriaxone. However, providers are often reluctant to de-escalate antibiotics without confirmed susceptibility testing, as there may be other mechanisms of antibiotic resistance in Gram-negative organisms. The objective of this evaluation was to measure the degree of congruence between BCID2 resistance mechanism detection and susceptibility testing by disk diffusion, and to validate the adequacy of the VCUHS ASP BCID2 treatment recommendations for Enterobacterales bacteremia. Methods: Patients with positive Enterobacterales BCID2 results from March 12 to June 19, 2023 were retrospectively identified. Organisms identified by BCID2 that were considered high-risk for clinically significant AmpC production due to an inducible AmpC gene (i.e., K. aerogenes, E. cloacae complex) were excluded. Results: A total of 270 results were included. The most commonly identified organism was E. coli (n = 139, 51.5%), followed by K. pneumoniae (n = 74, 27.4%). There were 27 (10%) isolates positive for CTX-M and 1 (0.4%) isolate positive for KPC. All CTX-M isolates were ceftriaxone resistant, and the KPC isolate was meropenem resistant. The remaining 242 isolates were negative for all resistance markers detected by BCID2. Of these, only 3 (1.2%) were resistant to ceftriaxone and notably, 8 (3.3%) were resistant to piperacillin/tazobactam. Overall, BCID2 CTX-M detection was 90% sensitive and 100% specific for predicting ceftriaxone resistance in Enterobacterales. Conclusion: CTX-M detection by BCID2 is highly sensitive and specific for predicting ceftriaxone resistance in Enterobacterales. CTX-M negative isolates were more often susceptible to ceftriaxone than to piperacillin/tazobactam, which is commonly used as empiric therapy for Gram-negative organisms at our institution. This highlights an excellent opportunity for safe and effective early de-escalation of antibiotics for treatment of Enterobacterales bacteremia.