Duke Antimicrobial Stewardship Outreach Network Research Articles

896. Cost-Avoidance Associated with Active Stewardship of Remdesivir

Abstract Background The COVID pandemic shifted antimicrobial stewardship resources at community hospitals. One reason for this shift was new COVID treatments, the first of which was remdesivir, which received initial emergency use authorization (EUA) for the treatment of COVID-19 in May 2020. The UNC Health Southeastern (UNC SEH) pharmacy director stewarded remdesivir by reviewing patients to ensure they met emergency use authorization (EUA) and guideline-based appropriateness criteria. The infectious diseases physician resolved any disputes regarding patient candidacy for remdesivir. The goal of remdesivir stewardship was to optimize care; however, the shift in workflow presented an unrecognized opportunity for stewards to reduce remdesivir costs. Methods The percentage of COVID patient admissions receiving remdesivir at UNC SEH for calendar years 2020 and 2021 was benchmarked against 32 community hospitals in the Duke Antimicrobial Stewardship Outreach Network (DASON) (Figure 1). UNC SEH purchasing data were used to calculate remdesivir expenditures for 2020 and 2021. Next, the anticipated cost if the hospital had prescribed remdesivir to the same percentage of admissions as the DASON mean was calculated. The difference was calculated to determine the cost avoidance achieved by having below average use of remdesivir (Table 1). Results At UNC SEH, 28.1% of COVID admissions received remdesivir in 2020 and annual remdesivir expenditures were $693,680. In 2021, 47.45% of COVID-19 admissions received remdesivir and drug expenditures were $1,248,000. The DASON mean % of COVID admissions receiving remdesivir in 2020 was 44.08% and 60.07% in 2021. A total cost avoidance of $726,407 was calculated based on the hospital’s below-benchmark use of remdesivir (Table 1). Conclusion UNC SEH achieved significant cost-savings in 2020 and 2021 due to active remdesivir stewardship. The team created a patient-centered model that focused on using drugs for the right patients and the organization realized cost-savings while ensuring that patients received therapy in accordance with remdesivir EUAs and published guidelines. Disclosures All Authors: No reported disclosures.

Use of Contact Networks to Estimate Potential Pathogen Risk Exposure in Hospitals

Person-to-person contact is important for the transmission of health care-associated pathogens. Quantifying these contact patterns is crucial for modeling disease transmission and understanding routes of potential transmission. To generate and analyze the mixing matrices of hospital patients based on their contacts within hospital units. In this quality improvement study, mixing matrices were created using a weighted contact network of connected hospital patients, in which contact was defined as occupying the same hospital unit for 1 day. Participants included hospitalized patients at 299 hospital units in 24 hospitals in the Southeastern United States that were part of the Duke Antimicrobial Stewardship Outreach Network between January 2015 and December 2017. Analysis was conducted between October 2021 and February 2022. The mixing matrices of patients for each hospital unit were assessed using age, Elixhauser Score, and a measure of antibiotic exposure. Among 1 549 413 hospitalized patients (median [IQR] age, 44 [26-63] years; 883 580 [56.3%] women) in 299 hospital units, some units had highly similar patterns across multiple hospitals, although the number of patients varied to a great extent. For most of the adult inpatient units, frequent mixing was observed for older adult groups, while outpatient units (eg, emergency departments and behavioral health units) showed mixing between different age groups. Most units mixing patterns followed the marginal distribution of age; however, patients aged 90 years or older with longer lengths of stay created a secondary peak in some medical wards. From the mixing matrices by Elixhauser Score, mixing between patients with relatively higher comorbidity index was observed in intensive care units. Mixing matrices by antibiotic spectrum, a 4-point scale based on priority for antibiotic stewardship programs, resulted in 6 major distinct patterns owing to the variation of the type of antibiotics used in different units, namely those dominated by a single antibiotic spectrum (narrow, broad, or extended), 1 pattern spanning all antibiotic spectrum types and 2 forms of narrow- and extended-spectrum dominant exposure patterns (an emergency room where patients were exposed to one type of antibiotic or the other and a pediatric ward where patients were exposed to both types). This quality improvement study found that the mixing patterns of patients both within and between hospitals followed broadly expected patterns, although with a considerable amount of heterogeneity. These patterns could be used to inform mathematical models of health care-associated infections, assess the appropriateness of both models and policies for smaller community hospitals, and provide baseline information for the design of interventions that rely on altering patient contact patterns, such as practices for transferring patients within hospitals.

Thoughts and beliefs of healthcare workers regarding the coronavirus disease 2019 (COVID-19) vaccine and which messaging themes might affect vaccine confidence and recommendation of the vaccine.

We surveyed healthcare workers within the Duke Antimicrobial Stewardship Outreach Network (DASON) to describe beliefs regarding coronavirus disease 2019 (COVID-19) vaccination and their decision-making process behind vaccination recommendations. In contrast to the type of messaging that appealed most on a personal level to the healthcare workers, they preferred a more generic message emphasizing safety and efficacy when making vaccination recommendations.

106. Pandemic Pinch: The Impact of COVID Response on Antimicrobial Stewardship Program (ASP) Resource Allocation

BackgroundThe COVID-19 pandemic placed a strain on inpatient clinical and hospital programs due to increased patient volume and rapidly evolving data on best COVID-19 management strategies. However, the impact of the pandemic on ASPs has not been well described. MethodsWe performed a cross-sectional electronic survey of stewardship pharmacy and physician leaders in 37 hospitals within the Duke Antimicrobial Stewardship Outreach Network (DASON) (community) and Duke/UNC Health systems (academic) in April-May 2021. The survey included 60 questions related to staffing changes, use of COVID-targeted therapies, related restrictions, and medication shortages.ResultsTwenty-seven facilities responded (response rate of 73%). Pharmacy personnel was reduced in 17 (63%) facilities by an average of 16%. Impacted pharmacy personnel included the stewardship lead in 15/17 (88.2%) hospitals. Converting to remote work was rare and only reported in academic institutions (n=2, 7.4%). ASP personnel were reassigned to non-stewardship duties in 12 (44%) hospitals with only half returning to routine ASP work as of May 2021. Respondents estimated that 62% of routine ASP activities were diverted during the time of the pandemic. Non-traditional, pandemic-related ASP activities included managing multiple drug shortages, of which ventilator support medications (91%) were most common affecting patient care at 52% of facilities. Steroid and hydroxychloroquine shortages were less frequent (44% and 22%, respectively). Despite staff reductions, pharmacists often served as primary contact for remdesivir approvals either using a criteria-based checklist at dispensing or as part of a dedicated phone approval team (Figure). Most (77%) hospitals used a criteria-based pharmacist review strategy after remdesivir FDA approval. Restriction processes for other COVID-19 therapies such as tocilizumab, hydroxychloroquine, and ivermectin were reported in 64% of hospitals.Remdesivir Allocation Strategy Proportion of facilities implementing specific remdesivir allocation strategies from the time of the first US Food and Drug Administration (FDA) Emergency Use Authorization (EUA) through FDA approvalConclusionPandemic response diverted routine ASP work and has not yet returned to baseline. Despite the reduction in pharmacy personnel due to the pandemic, the ASP pharmacy lead took on a novel and critical stewardship role throughout the pandemic exemplified by their involvement in novel treatment allocation for COVID patients.Disclosures Melissa D. Johnson, PharmD, MHS, Astellas (Consultant, Grant/Research Support)Charles River Laboratories (Grant/Research Support)Cidara (Consultant)Merck & Co (Consultant, Research Grant or Support)Paratek (Consultant)Pfizer (Consultant)Scynexis (Scientific Research Study Investigator)Theratechnologies (Consultant)UpToDate (Other Financial or Material Support, Author Royalties) Sonali D. Advani, MBBS, MPH, Nothing to disclose Rebekah W. Moehring, MD, MPH, UpToDate, Inc. (Other Financial or Material Support, Author Royalties)

Assessing feasibility of establishing antimicrobial stewardship programmes in two provincial-level hospitals in Vietnam: an implementation research study

ObjectivesTo investigate the feasibility of establishing hospital-based antimicrobial stewardship (AMS) programmes comprising action-planning, educational interventions and data feedback in two provincial-level hospitals in Viet Nam.Design and settingThis was an implementation...

598. Correlation of International Classification of Diseases (ICD) codes to initial provider-selected antibiotic indications in hospitalized adult patients within the Duke Antimicrobial Stewardship Outreach Network (DASON)

BackgroundProvider-selected antibiotic indications are a measure to help track antibiotic use, and facilitate stewardship activities. International Classification of Diseases 10th version (ICD-10) codes have been widely used in the medical field for a variety of purposes, including billing for reimbursement, disease epidemiology, administration, and research. The ability of these codes to accurately describe the true disease diagnosis has been questioned. The purpose of this study is to provide insight into correlation between ICD-10 codes and provider-selected antibiotic indications recorded upon antibiotic order entry.MethodsThis multicenter, retrospective cohort study was performed using data from 17 hospitals in the DASON network. Antibiotic orders during calendar year 2019 for inpatients ≥ 18 years of age that included an indication for use were extracted from the DASON antimicrobial stewardship assessment portal. Orders with the antibiotic indication category of prophylaxis (medical or surgical) and other were excluded. The primary outcome was agreement between antibiotic indication and any discharge ICD-10 code from the same hospital admission. Secondary analyses stratified results by antibiotic and indication. Descriptive statistics were used to describe outcomes.ResultsA total of 246,999 unique antibiotic orders were identified in 180,109 admissions. After removing prophylaxis (n=75,124) and other (n=36,359), 135,516 orders were included. Most orders did not have an ICD-10 code matching the prescriber indication (92,237 [68%]). All indications except HEENT (18% mismatch) and genitourinary infections (46% mismatch) lacked a corresponding diagnosis code in more than 50% of cases (Table 1). Urinary tract infections (93%), bloodstream infections (90%), and central nervous system infections (80%) showed the highest rates of mismatch among indications (Table 1).Table 1: Correlation of ICD-10 Codes to Provider Selected Indications ConclusionWe observed a high rate of mismatch between antibiotic indications and ICD-10 codes. Provider-selected antibiotic indications at the time of empiric treatment may be more reflective of diagnostic differential but is a poor indicator of ultimate patient diagnosis.DisclosuresRebekah W. Moehring, MD, MPH, Agency for Healthcare Quality and Research (Grant/Research Support)Centers for Disease Control and Prevention (Grant/Research Support) Melissa D. Johnson, PharmD, MHS, Charles River Laboratories (Grant/Research Support)Cidara (Consultant)Merck & Co (Scientific Research Study Investigator)Paratek (Consultant)Scynexis (Scientific Research Study Investigator)Shionogi (Consultant)UpToDate (Other Financial or Material Support, Royalties)

Identifying predictors of antimicrobial exposure in hospitalized patients using a machine learning approach.

Analysis and tracking of antimicrobial utilization (AU) are crucial in antimicrobial stewardship efforts which are used to find effective interventions for controlling antimicrobial resistance. In antimicrobial stewardship, standard risk adjustment models are needed for benchmarking appropriate AU and for fair inter-facility comparison. In this study we identify patient- and facility-level predictors of antimicrobial usage in hospitalized patients using a machine learning approach, which can be used to inform a risk adjustment model to facilitate assessment of AU. To our knowledge, this is the first time machine learning has been applied for this purpose. Patient admission records were retrieved from the Duke Antimicrobial Stewardship Outreach Network which include clinical data for 27 community hospitals in the southeastern United States. Candidate features (predictors) were then generated from these records. The number of features was reduced using a statistical approach, and missing values of the reduced feature set were imputed using bootstrapping and expectation-maximization algorithm. Finally, support vector regression (SVR) and cubist regression (CB) models were applied to find root-mean-square error values which were used to evaluate the selected feature set. The performance of the SVR and CB models was found to be better than that of linear null and negative binomial null models, thereby demonstrating the effectiveness of our selected features. Relevant patient- and facility-level predictors of antimicrobial usage in days of therapy were obtained and evaluated. The potential predictor set can be used in risk adjustment strategies for benchmarking antimicrobial use. One reason for the rapid emergence of antimicrobial resistance is inappropriate use of antibiotics in hospitalized patients. Identifying predictors of antimicrobial exposure using a machine learning technique can improve the use of AU, enhance patient health outcomes, and reduce the infection spread caused by antimicrobial-resistant organisms.

2089. Effect of the Duke Antimicrobial Stewardship Outreach Network (DASON): A Multi-Center Time Series Analysis

BackgroundDASON is a 30-member, community hospital network in the southeastern United States that supports the development and growth of local antibiotic stewardship programs (ASPs). Collaborative activities include on-site visits from liaison clinical pharmacists, data sharing for routine feedback and benchmarking, and educational programs.MethodsWe performed a retrospective cohort analysis of antibiotic use (AU) in 17 hospitals that participated in DASON for a minimum of 42 months during 2013–2018. Segmented negative binomial regression models were used to estimate the change in facility-wide AU after an initial 1-year assessment, planning, and ASP intervention initiation period. Baseline AU trend (1 to 12 months) was compared against AU following the first year (13 to 42 months). Monthly AU rates were measured in days of therapy (DOT) per 1,000 patient-days (pd). Models assessed overall AU and specific antibiotic groups, as defined by the National Healthcare Safety Network AU option. The models controlled for hospital size, presence of a pre-existing formal ASP upon network entry, and year of network entry.ResultsHospital data included a total of 2,988,930 pd over 5 years. Facility-wide AU was increasing during the first year of network entry and then began decreasing by 0.2% per month (P = 0.01, figure). Fluoroquinolone use was stagnant in year one and then decreased by 1.5% per month (P ≤ 0.001, figure). Antifungal agents were decreasing in year one and continued to decrease 0.7% per month thereafter (P = 0.03, figure). Agents predominantly used for resistant Gram-positive infections and broad-spectrum agents used for hospital-onset infections were increasing during year one and then attenuated afterward, though the slope change did not reach statistical significance. The presence of a pre-existing formal ASP was not a significant covariate in any model, while bed size and year of network entry significantly contributed to models of some antibiotic groups.ConclusionParticipation in DASON was associated with a decline in total AU and fluoroquinolone use, and a trend toward attenuated use of other broad-spectrum agents in community hospitals. Collaborative network experiences can help local ASPs achieve reductions in AU. Disclosures All authors: No reported disclosures.

996. Impact of Penicillin Allergy Labels on Carbapenem Use in a Multi-Center Study

BackgroundAntibiotic allergy labels lead to excess exposure to broad-spectrum antibiotics and can result in patient harm. We aimed to describe the prevalence of penicillin allergy labels (PAL) across a variety of hospital settings and its association with carbapenem exposure.MethodsWe performed a retrospective cohort analysis of inpatient admissions from 14 hospitals in the Duke Antimicrobial Stewardship Outreach Network (DASON) and Duke Health System from 2016 to 2018. Data were collected from the DASON central database which is derived from electronic health record extracts. PAL was defined from drug allergy documentation indicating any reaction to penicillin or its related agents, but did not include labels for other β-lactam agents (e.g., cephalosporin). Carbapenem exposure was defined as a binary variable indicating receipt of at least one dose of meropenem, ertapenem, doripenem or imipenem on an inpatient unit. The association between PAL and carbapenem exposure was assessed using multivariable logistical regression with candidate covariates including age, gender, comorbidity score, and exposure to intensive care or hematology/oncology unit. Hospital-level PAL prevalence was defined as the percentage of inpatient admissions. Hospital-level carbapenem use rates were assessed as days of therapy (DOT) per 1000 patient-days and stratified by PAL to understand the portion of use associated with PAL.ResultsOf the 727,168 admissions included in this study, 84,033 (11.6%) patients had a PAL. The majority of admissions with documented PAL were in patients >65 years old (47.9%, n = 40,240) and female (57.8%, n = 418,472). PAL was associated with a 2-fold higher risk of receipt of carbapenem (adjusted odds ratio 2.13, 95% CI 0.89–2.40, P < 0.0001). PAL prevalence varied among hospitals (median 14%, range 5–20%). Hospitals with antibiotic allergy-focused stewardship programs (ASP) had a similar PAL prevalence (median 13.8 vs. 15.9%, P = 0.08), but the percent of carbapenem DOT used in patients with PAL was similar (median 23% vs. 24%, P = 0.6).ConclusionPAL was associated with increased carbapenem exposure on the patient level. Allergy-focused ASP activities may affect PAL but it is unclear whether it reduces carbapenem use based on these observational data.Disclosures All authors: No reported disclosures.

262. Pediatric Antibiotic Use in the Duke Antimicrobial Stewardship Outreach Network

BackgroundThe Duke Antimicrobial Stewardship Outreach Network (DASON) was established in 2013 to provide antimicrobial stewardship resources to community hospitals in the Southeast. Pediatric patients in community hospitals may benefit from antimicrobial stewardship program (ASP) activities.MethodsAntibacterial use (AU) was reviewed using the DASON Antimicrobial Stewardship Assessment Portal, which includes filters for National Healthcare Safety Network (NHSN) unit types. We performed a retrospective review of AU in pediatric units from January 1 to December 31, 2017. AU was summarized by days of therapy (DOT) and percent of total DOT for specific unit types and agents. AU rates were reported by DOT/1,000 patient-days.ResultsA total of 41 pediatric units were included from the 28 hospital DASON cohort: 11 Neonatal Critical Care or Step Down Nurseries, eight Pediatric Medical/Surgical Wards, and 22 Well Baby Units. There were no pediatric (non-neonatal) critical care or oncology units. A total of 21,731 antibiotic DOT were attributable to pediatric units, accounting for 1.6% of all AU in the cohort. These include 5,585 (26%) DOT in Neonatal Critical Care (level II/III) Units, 4,898 (23%) in Pediatric Medical/Surgical Units, 3,910 (18%) in Well Baby Units, 3,307 (15%) in Neonatal Critical Care (level III) Units, 3,217 (15%) in Step Down Neonatal Nurseries (level II), and 814 (4%) in Pediatric Medical Wards. Ampicillin (7,229 DOT, 33%), gentamicin (6,320 DOT, 29%), ceftriaxone (1,750 DOT, 8%), and vancomycin (1,462, 7%) were the most common antibiotics administered.AU rates were 219 DOT/1,000 patient-days in children when compared with 979 in adults. Unit-specific rates ranged from 65 (Well Baby Units) to 1,081 DOT/1,000 patient-days (Pediatric Medical/Surgical Units). Rates in level II and III nurseries ranged from 302 to 697 DOT/1,000 patient-days.ConclusionPediatric patients accounted for a small proportion of AU in community hospitals. AU rates on pediatric medical/surgical units were comparable with adult units. Although rates were lower in neonatal units, these units accounted for 75% of pediatric AU. Antibiotic exposure in the neonatal period has been associated with short- and long-term outcomes, including necrotizing enterocolitis, obesity, and atopy. This population would benefit from a dedicated focus from community hospital ASPs.Disclosures All authors: No reported disclosures.

1629. Targeted Antimicrobial Use Admission Provides an Actionable Denominator for Antimicrobial Stewardship Programs Evaluating Inpatient Length of Therapy

BackgroundActionable, easy to interpret antibiotic use (AU) metrics provide antimicrobial stewardship programs (ASPs) with clear targets. Current aggregate AU metrics lack the ability to discriminate between long courses in a limited number of patients versus short courses in a large number of patients.MethodsWe developed a novel AU denominator termed “targeted antimicrobial use admission,” defined as an inpatient admission in which a selected agent or group of agents was administered. When used with length of therapy (LOT), it provides the average number of days patients receive the targeted agent(s) during inpatient hospital admissions. To demonstrate the added utility of this metric, we used descriptive statistics to compare it to LOT, LOT/1,000 patient days, LOT/1,000 admissions, and LOT/admission to quantify intravenous (IV) vancomycin use among 25 hospitals in the Duke Antimicrobial Stewardship Outreach Network (DASON) for calendar year 2017. The metric was also used to compare hospitals to one another and track durations at an example hospital over time.ResultsTotal LOT included 128,680 days of IV vancomycin (table). LOT/targeted antimicrobial use admission is the only metric that allows programs to quickly assess agent durations.Table:Comparison of IV Vancomycin Consumption by Metric Among 25 Hospitals in DASON, 2017LOT (days)LOT/AdmissionLOT/1,000 Patient DaysLOT/Targeted Antimicrobial Use AdmissionMean ± standard deviation5,147.2 ± 2,9940.4 ± 0.1111 ± 24.53.2 ± 0.5Median5,0930.4103.53.2Range512–13,0260.2–0.768.9–163.62.6–4.1ConclusionStewardship programs seeking to shorten durations of therapy can track this metric over time to determine the impact of their ASP efforts (Figure 1). The metric can also be used to compare average durations of IV vancomycin by hospital to determine when and if agent-focused audit and feedback or antibiotic timeouts may be useful (Figure 2). The network mean provides a target for agent-specific de-escalations, in days, for facilities with longer durations. LOT/targeted antimicrobial use admission provides an actionable metric for quantifying antimicrobial durations. This metric is easy to interpret and can feasibly be captured through the electronic prescribing record to aid in selecting ASP strategy. Disclosures All authors: No reported disclosures.

Can antibiotic De-escalation Be Measured Without Chart Review? A Proposed Electronic Definition

BackgroundAntimicrobial stewardship programs promote de-escalation: moving from broad to narrow spectrum agents and/or stopping antibiotics as more clinical data return. A standard definition of de-escalation objectively applied to electronic data could provide a means to assess stewardship improvement opportunities.MethodsWe performed a retrospective cohort study of de-escalation events among five hospitals from the Duke Health System and the Duke Antimicrobial Stewardship Outreach Network using 2016 electronic medication administration record data. Antibiotics were ranked into four categories: narrow spectrum (e.g., cefazolin), broad spectrum, extended spectrum, and agents typically targeted for protection (e.g., meropenem). Included patients were cared for on inpatient units, had antibiotic therapy for at least 2 days, and had at least 3 days of hospitalization after starting antibiotics. De-escalation was defined as reduction in either the number of antibiotics or rank measured at two time points: day 1 of initiation of antibiotic therapy and day 5 (or day of discharge if occurring on day 3 or 4). Escalation was an increase in either number or rank of agents. Unchanged was either no change or discordant directions of change in number and rank. For all categories, the outcome was percent among qualifying admissions. Descriptive statistics were used to describe de-escalation among hospitals, unit type, and ICD-10 diagnoses.ResultsAmong 39,226 included admissions, de-escalation occurred in 14,138 (36%), escalation in 5,129 (13%), and antibiotics were unchanged in 19,959 (51%) (Figure). Percent de-escalation was significantly different among hospitals (median 37%, range 31–39%, P < .001). Infectious diagnoses with lower rates of de-escalation included intra-abdominal infection (23%), skin and soft-tissue infection (28%), and ENT/upper respiratory tract infection (19%). Intensive care units had higher rates of both de-escalation and escalation (43% and 16%) when compared with non-ICU wards (35% and 13%, P < .001).ConclusionWe provided an objective, electronic definition of de-escalation and demonstrated variation among hospitals, units, and diagnoses. This metric may be useful for assessing stewardship opportunities.Disclosures All authors: No reported disclosures.

Benchmarking Antimicrobial Use in Emergency Departments among Community Hospitals in the Duke Antimicrobial Stewardship Outreach Network

BackgroundAntimicrobials are frequently administered in the Emergency Department (ED), and there are unique challenges to implementing antimicrobial stewardship in this setting. Benchmarking antimicrobial use (AU) in the ED may assist hospitals in identifying areas to target stewardship interventions. EDs are not currently included in the standardized antibiotic administration ratios calculated by the CDC Module. Therefore, we aimed to establish a method to compare AU among EDs across our network.MethodsThis descriptive cohort included hospitals participating in the Duke Antimicrobial Stewardship Outreach Network (DASON) with available electronic medication administration records from EDs for calendar year 2016. ED encounters were estimated using encounters data collected for LabID event reporting. Overall AU, AU by antimicrobial category, and AU by antimicrobial agent were calculated in days of therapy (DOT) per 1,000 ED encounters and then compared among hospitals using descriptive statistics. Outlying use for individual agents was defined as >95th percentile.ResultsThirteen community hospitals in the southeastern United States provided AU data for over 724,627 encounters (median 57,199, range 29,063–86,574). Median overall AU was 206 DOT/1000 ED encounters and showed variation among hospitals (interquartile range (IQR) 180–231) (Figure 1). The majority of administered agents were antibacterials (96.9%), followed by antifungals (1.18%), antivirals (0.13%), and other (0.12%). Antimicrobial categories showing greatest variation among EDs included antifungals (coefficient of variation (CV) 57.47, median 2.04, IQR 1.39-3.36) and antipseudomonal β-lactams (CV, 44.8, median 19.3, IQR 14.07-21.76). Outlying use in individual EDs were identified for ertapenem, ceftaroline, daptomycin, and fluconazole (Figures 2 and 3).ConclusionWe observed large variability in AU in EDs among acute care community hospitals and identified several outliers for certain agents among hospital EDs using the metric DOT per 1000 ED encounters. These data will help inform future stewardship interventions at these hospitals.Disclosures All authors: No reported disclosures.

Variability in Antimicrobial Use Among Community Hospitals in the Duke Antimicrobial Stewardship Outreach Network

Variability in Antimicrobial Use Among Community Hospitals in the Duke Antimicrobial Stewardship Outreach Network

219Characteristics of Antimicrobial Stewardship (AS) Activities in Community Hospitals Upon Enrollment in the Duke Antimicrobial Stewardship Outreach Network (DASON)

219Characteristics of Antimicrobial Stewardship (AS) Activities in Community Hospitals Upon Enrollment in the Duke Antimicrobial Stewardship Outreach Network (DASON)