During the coronavirus disease 2019 pandemic, mathematical modeling has been widely used to understand epidemiological burden, trends, and transmission dynamics, to facilitate policy decisions, and, to a lesser extent, to evaluate infection prevention and control (IPC) measures. This review highlights the added value of using conventional epidemiology and modeling approaches to address the complexity of healthcare-associated infections (HAI) and antimicrobial resistance. It demonstrates how epidemiological surveillance data and modeling can be used to infer transmission dynamics in healthcare settings and to forecast healthcare impact, how modeling can be used to improve the validity of interpretation of epidemiological surveillance data, how modeling can be used to estimate the impact of IPC interventions, and how modeling can be used to guide IPC and antimicrobial treatment and stewardship decision-making. There are several priority areas for expanding the use of modeling in healthcare epidemiology and IPC. Importantly, modeling should be viewed as complementary to conventional healthcare epidemiological approaches, and this requires collaboration and active coordination between IPC, healthcare epidemiology, and mathematical modeling groups.

Through the Centers for Medicare and Medicaid Services Promoting Interoperability Program, more hospitals will be reporting to the National Healthcare Safety Network Antimicrobial Use (AU) Option. We highlight the next steps and opportunities for measurement of AU to optimize prescribing.

Antimicrobial resistance is a global and pressing problem that requires large-scale, federal coordination of efforts and tailored local interventions and surveillance. Given the urgency of the threat, many countries now have national policies to reduce inappropriate antimicrobial use. However, few countries have followed this with resources at the institutional level to support the implementation of practices to achieve this goal. In the United States, accreditation bodies such as Centers for Medicare and Medicaid Services and The Joint Commission have added antimicrobial stewardship standards to encourage uptake of antimicrobial stewardship programs (ASPs).

Background: Antimicrobial stewardship (AMS) interventions have predominantly involved inpatient antimicrobial therapy. However, for many hospitalized patients, most antibiotic use occurs after discharge, and unnecessarily prolonged courses of therapy are common. Patient transition from hospitalization to discharge represents an important opportunity for AMS intervention. We describe patterns of antibiotic use selection and duration of therapy (DOT) for common infections including discharge antibiotics. Methods: This retrospective cross-sectional analysis was derived from an IRB-approved, multihospital, quasi-experiment at a 5-hospital health system in southeastern Michigan. The study population included patients discharged from an inpatient general and specialty practice ward on oral antibiotics from November 2018 through April 2019. Patients were included with the following diagnoses: skin and soft-tissue infections (SSTIs), community-acquired pneumonia (CAP), hospital-acquired pneumonia (HAP), respiratory viral infections, acute exacerbation of chronic obstructive pulmonary disease (AECOPD), intra-abdominal infections (IAIs), and urinary tract infections (UTIs). Other diagnoses were excluded. Data were extracted from medical records including antibiotic indication, selection, and duration, as well as patient characteristics. Results: In total, 1,574 patients were screened and 800 patients were eligible for inclusion. The most common antibiotic indications were respiratory tract infections, with 487 (60.9%) patients. These included 165 AECOPD cases (20.6%) and 200 CAP cases (25%) with no multidrug resistant organism (MDRO) risk factors; 57 patients (7.1%) with MDRO risk factors; HAP in 7 patients (0.9%); and influenza in 58 patients (7.2%). Also, 205 (25.6%) patients were diagnosed with UTIs: 71 with cystitis (8.9%), 86 (10.8%) with complicated UTI (cUTI), and 48 (6%) with pyelonephritis. Furthermore, 125 patients (15.6%) were diagnosed with SSTI: 59 (7.4%) purulent and 66 (8.3%) nonpurulent. 31 (3.9%) patients had an IAI. The most commonly used antibiotics were cephalosporins in 536 patients (67%), azithromycin in 252 patients (31.5%), and fluroquinolones and tetracyclines in 231 patients (28.9%). Fluroquinolones were the most frequent antibiotic prescribed at discharge in 210 patients (26.3%). Figure 1 displays the average DOT relative to specific indications. The median duration of total antibiotic therapy exceeded institutional guideline recommendation for multiple conditions, including AECOPD (7 days vs recommended 5 days), CAP with COPD (8.3 vs 7 days ), CAP without COPD (7.7 vs 5 days), and pyelonephritis (11 vs 7–10 days). Also, 269 (33.6%) patients received unnecessary therapy; 218 (27.3%) of these were due to excess duration. Conclusions: Among a cross-section of hospitalized patients, the average DOT, including after discharge, exceeded the optimal therapy for many patients. Further understanding of patterns and influences of antibiotic prescribing is necessary to design effective AMS interventions for improvement.

Funding: This work was completed under CDC contract number 200-2018-02928.

Disclosures: None

Background: The CDC NHSN launched the Antimicrobial Use Option in 2011. The Antimicrobial Use Option allows users to implement risk-adjusted antimicrobial use benchmarking within- and between- facilities using the standardized antimicrobial administration ratio (SAAR) and to evaluate use over time. The SAAR can be used for public health surveillance and to guide an organization’s stewardship or quality improvement efforts. Methods: Antimicrobial Use Option enrollment grew through partner engagement, targeted education, and development of data benchmarking. We analyze enrollment over time and discuss key drivers of participation. Results: Initial 2011 Antimicrobial Use Option enrollment efforts awarded grant Funding: to 4 health departments. These health departments partnered with hospitals, which encouraged vendors to build infrastructure for electronic antimicrobial use reporting. CDC supported vendors through outreach and education. In 2012, with CDC support, Veterans’ Affairs (VA) Informatics, Decision-Enhancement, and Analytic Sciences Center and partners began implementation of Antimicrobial Use Option reporting and validation of submitted data. These early efforts led to enrollment of 64 facilities by 2014 (Fig. 1). As awareness of the antimicrobial use option grew, we focused on facility engagement and development of benchmark metrics. A second round of grant Funding: in 2015 supported submission to the Antimicrobial Use Option from additional facilities by Funding: a vendor, a healthcare system, and an antimicrobial stewardship network. In 2015, CMS recognized the Antimicrobial Use Option as a choice for public health registry reporting under Meaningful Use Stage 3, resulting in an increase in participating hospitals. Antimicrobial Use Option enrollment increased in 2015 (n = 120), coinciding with national prioritization of antimicrobial stewardship. In 2016, the SAAR, was released in NHSN. We leveraged the SAAR to encourage participation from additional facilities and began quarterly calls to encourage continued participation from existing users. In 2016, the Department of Defense began submitting data to the Antimicrobial Use Option, resulting in 207 facilities enrolled in 2016, which grew to 616 in 2017. As of November 2019, 12 vendors self-report submission capabilities and 1,470 facilities, of ~6,800 active NHSN participants, are enrolled in the Antimicrobial Use Option. Two states have passed requirements regulating Antimicrobial Use Option reporting with Tennessee’s requirement going into effect in 2021. Conclusions: The Antimicrobial Use Option offers evidence that collaboration with partners, and leveraging of benchmarking metrics available to a national surveillance system can lead to increased voluntary participation in surveillance of high-priority public health data. Moving forward, we will continue expanding analytic capabilities and partner engagement.

Funding: None

Disclosures: None

Background: Bedside nurses have been recognized as potential antibiotic stewards; however, data on effective ways that nurses can contribute to stewardship activities in acute-care hospitals are scarce. Methods: A nurse-driven urine culture intervention to improve urine culture ordering practices was implemented in a medicine and a neurocritical care unit (NCCU) at The Johns Hopkins Hospital. Bedside nurses implemented an algorithm (Fig. 1) developed by the antibiotic stewardship program (ASP) to review the appropriateness of urine culture and to guide discussions with ordering providers regarding unnecessary urine cultures. Nurses received in-person training by an ASP physician champion on how to use the algorithm and education on the definition and indications for evaluation for asymptomatic bacteriuria and urinary tract infections. The ASP physician periodically visited the units to address concerns and questions. In both units, a nurse champion was identified to serve as liaison between the ASP and bedside nurses, and physician support was obtained before the intervention. The pre- and postintervention periods for the medicine unit were September 2017–August 2018 and September 2018–August 2019, respectively. For the NCCU, these periods were September 2018–February 2019 and March 2019–September 2019, respectively. Trends in urine cultures per 100 patient days (PD) were examined with statistical process charts and compared before and after the intervention using a standard incident ratio (IRR) and Poisson regression. Results: In total, 327 urine cultures were collected in the medicine unit and 293 in the NCCU over the study period. Although the intervention led to a significant 34% reduction in the rate of urine cultures on the medicine unit (from 2.3 to 1.5 cultures/100 PD; IRR, 0.66; 95% CI, 0.50–0.87; P < .01), the number of urine cultures remained without a significant change in the NCCU (from 4.5 to 3.7 cultures/100 PD; IRR, 0.89; 95% CI, 0.65–1.22; P = .48) (Fig. 2). Conclusions: Algorithm-based, nurse-driven review of urine culture indications reduced urine cultures on a medicine unit but not in a neurosciences ICU. Success on the medicine unit may have been driven by highly engaged nurse and physician champions and by patients being able to respond questions about symptoms. The following factors might have impacted results on NCCU: presence of conflicting protocols (eg, panculturing patients every 48 hours per a hypothermia protocol), unit tradition (eg, obtaining cultures to assess treatment response), perception of greater risk benefit in NCCU patients, and unit dynamics (open unit with other primary services placing orders for patients). Unit and team dynamics can affect effective implementation of antimicrobial stewardship interventions by nurses.

Funding: None

Disclosures: None

Background: To provide a standardized, risk-adjusted method for summarizing antimicrobial use (AU), the Centers for Disease Control and Prevention developed the standardized antimicrobial administration ratio, an observed-to-predicted use ratio in which predicted use is estimated from a statistical model accounting for patient locations and hospital characteristics. The infection burden, which could drive AU, was not available for assessment. To inform AU risk adjustment, we evaluated the relationship between the burden of drug-resistant gram-positive infections and the use of anti-MRSA agents. Methods: We analyzed data from acute-care hospitals that reported ≥10 months of hospital-wide AU and microbiologic data to the National Healthcare Safety Network (NHSN) from January 2018 through June 2019. Hospital infection burden was estimated using the prevalence of deduplicated positive cultures per 1,000 admissions. Eligible cultures included blood and lower respiratory specimens that yielded oxacillin/cefoxitin–resistant Staphylococcus aureus (SA) and ampicillin-nonsusceptible enterococci, and cerebrospinal fluid that yielded SA. The anti-MRSA use rate is the total antimicrobial days of ceftaroline, dalbavancin, daptomycin, linezolid, oritavancin, quinupristin/dalfopristin, tedizolid, telavancin, and intravenous vancomycin per 1,000 days patients were present. AU rates were modeled using negative binomial regression assessing its association with infection burden and hospital characteristics. Results: Among 182 hospitals, the median (interquartile range, IQR) of anti-MRSA use rate was 86.3 (59.9–105.0), and the median (IQR) prevalence of drug-resistant gram-positive infections was 3.4 (2.1–4.8). Higher prevalence of drug-resistant gram-positive infections was associated with higher use of anti-MRSA agents after adjusting for facility type and percentage of beds in intensive care units (Table 1). Number of hospital beds, average length of stay, and medical school affiliation were nonsignificant. Conclusions: Prevalence of drug-resistant gram-positive infections was independently associated with the use of anti-MRSA agents. Infection burden should be used for risk adjustment in predicting the use of anti-MRSA agents. To make this possible, we recommend that hospitals reporting to NHSN’s AU Option also report microbiologic culture results.

Funding: None

Disclosures: None

Background: Healthcare-associated infections (HAIs) are a serious threat to patient safety; they account for substantial morbidity, mortality, and healthcare costs. Healthcare practices, such as inappropriate use of antimicrobials, can also amplify the problem of antimicrobial resistance. Data collected to target HAI prevention and antimicrobial stewardship efforts and measure progress are an important resource for assuring transparency and accountability in healthcare, tracking adverse outcomes, investigating healthcare practices that may spread or protect against disease, detecting and responding to the spread of resistant pathogens, preventing infections, and saving lives. Methods: We discuss 3 healthcare-associated infection and antimicrobial Resistant infection (HAI-AR) reporting types: NHSN HAI-AR reporting, reportable diseases, and nationally notifiable diseases. HAI-AR reporting requirements outline facilities and data to report to NHSN and the health department to comply with state laws. Reportable diseases are those that facilities, providers, and laboratories are required to report to the health department. Nationally notifiable diseases are those reported by health departments to the CDC for nationwide surveillance and analysis as determined by Council of State and Territorial Epidemiologists (CSTE) and the CDC. Data presented are based on state and federal policy; NHSN data are based on CDC reporting statistics. Results: Since the 2005 launch of the CDC NHSN and publication of federal advisory committee HAI reporting guidance, most states have established policies stipulating healthcare facilities in their jurisdiction report HAIs and resistant infections to the NHSN to gain access to those data, increasing from 2 states in 2005, to 18 in 2010, and to 36 states, Washington, DC, and Philadelphia in 2019. Reporting policies and NHSN participation expanded greatly following the 2011 inception of CMS HAI quality reporting requirements, with several states aligning state requirements with CMS reporting. States listing carbapenem-resistant Enterobacteriaceae (CRE) as a reportable disease increased from 7 in 2013 to 41 states and the District of Columbia in 2019. Vancomycin-intermediate and vancomycin-resistant Staphylococcus aureus (VISA/VRSA) was added as a nationally notifiable disease in 2004, carbapenemase-producing CRE (CP-CRE) was added in 2018, and Candida auris clinical infections were added in 2019. The CDC and most jurisdictions with HAI reporting mandates issue public reports based on aggregate state data and/or facility-level data. States may also alert healthcare providers and health departments of emerging threats and to assist in notifying patients of potential exposure. Conclusions: Through efforts by health departments, facilities, patient advocates, partners, the CDC, and other federal agencies, HAI-AR reporting has steadily increased. Although reporting laws and data uses vary between jurisdictions, data provided serves as valuable tools to inform prevention.

Funding: None

Disclosures: None

Background: Patients with a penicillin/aminopenicillin (PCN) allergy label are more likely to receive non–β-lactam antibiotics and to experience worse clinical outcomes. Given that nurses are often first to interact with patients, we pilot tested a nurse-driven quality improvement initiative to improve PCN allergy documentation and increase β-lactam use. Methods: We conducted a before-and-after study on a labor and delivery unit at The Johns Hopkins Hospital (JHH) from May 2018 to September 2019. Patients aged 18 years with a PCN allergy were included. The intervention included (1) the use of an algorithm developed by the antimicrobial stewardship team to assist nurses in obtaining accurate PCN allergy histories (Fig. 1), (2) identification of a nurse champion to facilitate implementation of the algorithm, and (3) in-person education by a stewardship physician regarding the importance and impact of adequate PCN allergy documentation on clinical outcomes. Readmissions were counted as separate encounters. The primary outcome was improved allergy documentation (either fewer blank documentations, nonspecified rash reactions, drug intolerance documentations (eg, isolated nausea), documentation of signs and symptoms of anaphylaxis not specified as such). The secondary outcome was β-lactam use. Categorical variables were compared using the 2 test and continuous variables were compared with the Student t test. Severe allergic reactions were defined as anaphylaxis, severe skin reactions (eg, Stevens-Johnson syndrome), and organ involvement (eg, hepatitis). Results: Overall, 382 patient admissions were included, 305 in the preintervention (May 2018 to May 2019) and 77 in the postintervention period (June 2019 to September 2019). Mean age and length-of-stay were 30 years and 4 days, respectively, for both periods. The proportion of admitted patients with a PCN allergy label was 8% and 7% for pre- and postintervention periods. Documentation findings in the pre- and postintervention periods respectively were as follows: blank documentation 11% and 12% (P = .89), documentation of specified rashes 0.6% and 1.3% (P = .56), documentation of drug intolerance 11% and 8% (P = .39), documentation of reactions that were indicative of anaphylaxis but not documented specifically as anaphylaxis 8% and 13% (P = .20). Among patients with a documented PCN allergy who received antibiotics, 83 of 177 (47%) and 27 of 43 (63%) received β-lactams (P = .01) in the pre- and postintervention periods, with cefazolin being the antibiotic most commonly used in both periods. Conclusions: Nursing education and an algorithm did not result in significant improvements in PCN allergy documentation in the 3 months after implementation. More data collection is planned to assess the impact of the intervention.

Funding: None

Disclosures: None

Background: Inappropriate antibiotic prescription leads to increased Clostridiodes difficile infections, adverse effects including organ toxicity, and generation of antibiotic-resistant bacteria. Despite efforts to improve antibiotic use in acute-care settings, unnecessary and inappropriate prescription still occur in 30%–50% of patients. Objectives: We assessed factors associated with inappropriate antibiotic prescription at 2 time points: (1) initial, empiric therapy and (2) 3–5 days after therapy initiation. Methods: As part of a multicenter study investigating strategies to reduce antibiotic therapy after 3–5 days of use, antibiotic prescription data were collected from 11 adult and pediatric intensive care and general medical units at 6 hospitals in Maryland in 2014 and 2015. We performed a retrospective cohort study of all hospitalized patients who received any of 23 common antibiotics for at least 3 days. Each medical record was reviewed for demographics, admission and discharge dates, patient comorbidities, and antibiotic regimen by at least 1 infectious disease physician or pharmacist. Classification of antibiotic inappropriateness was based on each institution’s guidelines and standards. Bivariate analyses were performed using logistic regression for both initial therapy and therapy at days 3–5. Multivariable logistic regression was performed using covariates meeting the significance level of P < .05. Results: In total, 3,436 antibiotic courses were assessed at time of initial therapy, and 1541 regimens were continued and reviewed again at days 3–5 of therapy. For the initial therapy, 1,255 regimens (37%) were inappropriate; 45% of these were considered unnecessary and 41% were too broad in spectrum. In the multivariable regression, older age and antibiotic prescription during the summer were associated with the receipt of inappropriate antibiotics (Table 1). Having end-stage renal disease as a comorbid condition was protective against inappropriate use. At days 3–5 of therapy, 688 (45%) of the antibiotic courses were inappropriate. Reasons regimens were considered inappropriate included unnecessary antibiotic prescriptions (49%) and antibiotics being too broad (38%). Older age and receiving cefepime or piperacillin-tazobactam on day 3 of therapy were factors associated with inappropriate use (Table 2). Having undergone a transplant or a surgical procedure was protective of inappropriate antimicrobial use at days 3–5 of therapy. Conclusions: Older patients are more likely to receive inappropriate antibiotics at both initial regimen and 3–5 days later. Patients receiving cefepime or piperacillin-tazobactam are at greater risk of receiving inappropriate antibiotics at days 3–5 due to failure to de-escalate. Antibiotic stewardship strategies targeting these patient populations may limit inappropriate use.

Funding: None

Disclosures: None

Background: Unnecessary and prolonged antibiotic use is an important driver of antimicrobial resistance, increasing patient harm and resource utilization. Antimicrobials prescribed at hospital discharge represent an important opportunity to intervene and optimize therapy. Objective: We describe the implementation of a pharmacist-led multidisciplinary antimicrobial stewardship (AMS) intervention at transition of care (TOC) to improve antibiotic selection and duration. Methods: This intervention an IRB-approved multihospital, quasi-experimental, 3-phase stepped-wedge project in a 5-hospital health system. The setting included a large, urban, academic medical center in Detroit, Michigan, and 4 community hospitals in southeastern Michigan. AMS is provided by a pharmacist and infectious diseases physician at each site. For the AMS TOC intervention, pharmacists implemented 3 strategies: (1) early identification of patients to be discharged on oral antibiotics; (2) collaborative planning and communication regarding guideline-recommended antibiotic selection and duration; and (3) facilitation of discharge antibiotic prescription with appropriate stop date. Process improvements were modified to fit the academic and community hospital practice models. The process was implemented in general and specialty practice wards at each hospital site. Prior to implementation in October 2018, pharmacists were trained on tools to standardize identification, collaboration, and documentation. Pocket cards were used to augment education and electronic medical record (EMR) templates standardized documentation. Physicians and nurses on participating units were educated on the rationale and process. Following initiation, ongoing feedback was provided regularly to pharmacists to discuss challenges and to identify solutions. Process measures included the total number of patients receiving the intervention monthly, as indicated by pharmacist AMS TOC notes placed. Protocol adherence was evaluated in 25 randomly selected patients in each study phase each month. Adherence was defined as a pharmacist preparing discharge prescriptions and a placing note in the EMR. Results: Over the study period, 1,558 patient encounters received AMS TOC facilitation by a pharmacist. Monthly protocol adherence ranged from 29% to 87% (higher in academic institutions than community) (Fig. 1). Months of low protocol adherence were associated with times of reduced staffing and onboarding a large group of new employees or trainees. Additional barriers included discharges over weekends. The most common area needing clarification was how to count days of therapy to determine the appropriate stop date. A guide of how to count days of therapy was created to assist. Conclusions: Pharmacist-led antimicrobial stewardship at discharge is a feasible intervention in both academic and community settings. Identifying potential barriers and assessing strategies with multidisciplinary healthcare teams allows for optimal implementation and intervention rollout.

Funding: This work was completed under CDC contract number 200-2018-02928.

Disclosures: None

Background: Antimicrobial stewardship (AMS) is recommended in hospital, postacute, and outpatient settings. Transitions of care (TOC) are important in each of these settings; however, AMS efforts during TOC have been limited. Beginning in October 2018, we sequentially implemented a pharmacist-led multidisciplinary review of oral antimicrobial therapy prescribed at hospital discharge from general and specialty medicine wards across a health system. Pharmacists facilitated data input of discharge prescriptions following early identification and collaborative discussion of patients to be discharged on oral antimicrobials The purpose of this study was to evaluate the impact of AMS during TOC. Methods: This project was an IRB-approved stepped-wedge, quasi-experimental study in a 5-hospital health system that included hospitalized adults with skin, urinary, intra-abdominal, and respiratory tract infections who had been discharged from general and specialty wards with oral antimicrobials. Patients with complicated infections, neutropenia, or who were transferred from an outside hospital were excluded. The primary end point was optimization of antimicrobial therapy at time of hospital discharge, defined by correct selection, dose, and duration according to institutional guidance. Outcomes were compared before and after the intervention. Results: In total, 800 patients were included: 400 in the preintervention period and 400 in the postintervention period. Among this cohort, 252 (63%) received the intervention by a pharmacist per protocol during TOC. Patients had similar comorbid conditions before and after the intervention. Preintervention patients were more likely to be discharged from community hospitals. Before the intervention, 36% of discharge regimens were considered optimized, compared to 81.5% after the intervention (P < .001); this difference was largely driven by a reduction in patients receiving a duration of therapy beyond the clinical indication (44.5 vs 10%; P < .001). We observed similar clinical resolution, 30-day readmission, and adverse drug events (ADEs) between the pre- and postintervention periods. Postdischarge antimicrobial duration of therapy was reduced from 4 days (range, 3–5) to 3 days (range, 2–4) (P < .001) Severe ADEs occurred more frequently in the preintervention group (9 vs 3.3%; P = .001), which was driven by isolation of multidrug-resistant pathogens (7 vs 2.5%; P = .003) and Clostridioides difficile (1.8 vs 0.5%; P = .094). Patients who received optimal therapy at discharge were less likely to develop an ADE (aOR, 0.530; 95% CI, 0.363–0.773). Conclusions: Implementation of an AMS TOC protocol reduced antimicrobial days, optimized therapy selection, and reduced duration. This intervention was associated with improved safety without compromise of clinical effectiveness. To increase patient safety, AMS programs should target antimicrobial optimization during TOC.

Funding: This work was completed under CDC contract number 200-2018-02928.

Disclosures: None

Background: Assessing antimicrobial use (AU) appropriateness isa cornerstone of antimicrobial stewardship, largely accomplished through time-intensive manual chart review of specific agents or diagnoses. Efforts to evaluate appropriateness have focused on assessing the appropriateness of an entire treatment course. An electronic measure was developed to assess the appropriateness of each day of inpatient AU leveraging electronic health record data. Methods: We extracted contextual data, including risk factors for resistant organisms, allergies, constitutional signs and symptoms from diagnostic and procedural codes, and microbiological findings, from the electronic health records of patients in Veterans’ Health Administration inpatient wards reporting data to the National Healthcare Safety Network (NHSN) AU option from 2017–2018. Only the antibacterial categories shown in Figure 1 were included. Respiratory, urinary tract, skin and soft-tissue, and other infection categories were defined and applied to each hospital day. Algorithm rules were constructed to evaluate AU based on the clinical context (eg, in the ICU, during empiric therapy, drug–pathogen match, recommended drugs, and duration). Rules were drawn from available literature, were discussed with experts, and were then refined empirically. Generally, the rules allowed for use of first-line agents unless risk factors or contraindications were identified. AU was categorized as appropriate, inappropriate, or indeterminate for each day, then aggregated into an overall measure of facility-level AU appropriateness. A validation set of 20 charts were randomly selected for manual review. Results: Facility distribution of appropriateness, inappropriateness, and indeterminate AU by 4 of the adult, 2017 baseline NHSN Standardized Antimicrobial Administration Ratio (SAAR) categories are shown in Figure 1. The median facility-level inappropriateness across all SAAR categories was 37.2% (IQR, 29.4%–52.5%). The median facility-level indeterminate AU across all SAAR categories was 14.4% (IQR, 9.1%–21.2%). Chart review of 20 admissions showed agreement with algorithm appropriateness and inappropriateness in 95.4% of 240 antibacterial days.

Conclusions: We developed a comprehensive, flexible electronic tool to evaluate AU appropriateness for combinations of setting, antibacterial agent, syndrome, or time frame of interest (eg, empiric, definitive, or excess duration). Application of our algorithm in 2 years of VA acute-care data suggest substantial interfacility variability; the highest rates of inappropriateness were for anti-MRSA therapy. Our preliminary chart review demonstrated agreement between electronic and manual review in >95% of antimicrobial days. This approach may be useful to identify potential stewardship targets, in the development of decision support systems, and in conjunction with other metrics to track AU over time.

Funding: None

Disclosures: None

Documentation of antibiotic indication provides helpful information for antimicrobial stewardship, but accuracy is not understood. Review of 396 antibiotic orders in a pediatric ICU and adult medicine step-down unit found 90% agreement between provider-selected indication and independent review. Prompts to enter antibiotic indication during order entry provide largely accurate information.

Infect Control Hosp Epidemiol 2018;39:111–113

The antimicrobial use (AU) option within the National Healthcare Safety Network summarizes antimicrobial prescribing data as a standardized antimicrobial administration ratio (SAAR). A hospital’s antimicrobial stewardship program found that greater involvement of an infectious disease physician in prospective audit and feedback procedures was associated with reductions in SAAR values across multiple antimicrobial categories.

Infect Control Hosp Epidemiol 2017;38:721–723