Background In 2014, the Centers for Disease Control and Prevention (CDC) released the Core Elements of Hospital Antibiotic Stewardship Programs (ASPs) and began monitoring uptake through the National Healthcare Safety Network (NHSN) Annual Hospital Survey. In 2019, CDC updated the Core Elements and in 2022 released the Priorities for Hospital Core Element Implementation. We describe Core Element uptake from 2014 to 2021, provide a snapshot of specific ASP practices in acute care hospitals in 2021, and describe how we plan to monitor stewardship moving forward.Methods We used the NHSN Annual Hospital Survey to summarize facility demographics and ASP practices and to monitor uptake of Core Elements. Questions have been updated over time, so not all data could be compared across years.Results Uptake of all 7 Core Elements increased from 41% in 2014 to 95% in 2021. Uptake of all 6 Priority Elements was 10% in 2021, though 46% of hospitals met 4 or 5 of the possible 6 elements. Antibiotic stewardship was specifically listed in a contract or job description for about 60% of program leaders. The percentage of physician-pharmacist co-led programs rose from 23% to 64%. Seventy-six percent of hospitals reported implementing audit with feedback interventions.Conclusions With nearly all acute care hospitals reporting uptake of the 7 Core Elements in 2021, and with more evidence for which ASP practices are most effective, the Priorities for Hospital Core Element Implementation were released in 2022 to help enhance the quality and impact of existing ASPs. Substantial progress has been made in the implementation of CDC's Core Elements between 2014 and 2021. Results of the National Healthcare Safety Network Annual Hospital Survey highlight this progress and shed light on areas where additional antibiotic stewardship work is needed.

METHODS:Outpatient hemodialysis facilities report BSI events to NHSN. Pooled mean rates with 95% CI were calculated overall and for each type of vascular access (arteriovenous (AV) fistula, AV graft, or a central venous catheter (CVC)). Standardized infection ratios were calculated as observed BSI events divided by the predicted number of events based on national aggregate data. Median facility-level standardized infection ratios and 95% confidence intervals (CIs) were stratified by state and US territory.RESULTS:During 2020, 7,183 outpatient hemodialysis facilities reported data for 5,235,234 patient months with 15,181 BSI events. Pooled mean rates per 100 person-months were 0.29 (95% CI, 0.29-0.30) overall, 0.80 (95% CI, 0.78-0.82) for CVC, 0.12 (95% CI, 0.12-0.12) for AV fistula, 0.21 (95% CI, 0.20-0.22) for AV graft, and 0.28 (95% CI, 0.19-0.40) for other access types. The national standardized infection ratio was 0.40 (95% CI, 0.39-0.41). South Dakota had a standardized infection ratio significantly higher than one (1.34; 95% CI, 1.11 - 1.62). Fifty-one of 54 states and territories had BSI standardized infection ratio significantly lower than one.CONCLUSIONS:In 2020, the median standardized infection ratio for BSI in US outpatient hemodialysis facilities was lower than predicted overall and in almost all states and territories. An elevated standardized infection ratio was identified in South Dakota.

Antimicrobial use data reported to the National Healthcare Safety Network's Antimicrobial Use and Resistance Module between January 2019 and July 2022 were analyzed to assess the impact of the COVID-19 pandemic on inpatient antimicrobial use.

Racial and ethnic minorities are disproportionately affected by end-stage kidney disease (ESKD). ESKD patients on dialysis are at increased risk for Staphylococcus aureus bloodstream infections, but racial, ethnic, and socioeconomic disparities associated with this outcome are not well described.Surveillance data from the 2020 National Healthcare Safety Network (NHSN) and the 2017-2020 Emerging Infections Program (EIP) were used to describe bloodstream infections among patients on hemodialysis (hemodialysis patients) and were linked to population-based data sources (CDC/Agency for Toxic Substances and Disease Registry [ATSDR] Social Vulnerability Index [SVI], United States Renal Data System [USRDS], and U.S. Census Bureau) to examine associations with race, ethnicity, and social determinants of health.In 2020, 4,840 dialysis facilities reported 14,822 bloodstream infections to NHSN; 34.2% were attributable to S. aureus. Among seven EIP sites, the S. aureus bloodstream infection rate during 2017-2020 was 100 times higher among hemodialysis patients (4,248 of 100,000 person-years) than among adults not on hemodialysis (42 of 100,000 person-years). Unadjusted S. aureus bloodstream infection rates were highest among non-Hispanic Black or African American (Black) and Hispanic or Latino (Hispanic) hemodialysis patients. Vascular access via central venous catheter was strongly associated with S. aureus bloodstream infections (NHSN: adjusted rate ratio [aRR] = 6.2; 95% CI = 5.7-6.7 versus fistula; EIP: aRR = 4.3; 95% CI = 3.9-4.8 versus fistula or graft). Adjusting for EIP site of residence, sex, and vascular access type, S. aureus bloodstream infection risk in EIP was highest in Hispanic patients (aRR = 1.4; 95% CI = 1.2-1.7 versus non-Hispanic White [White] patients), and patients aged 18-49 years (aRR = 1.7; 95% CI = 1.5-1.9 versus patients aged ≥65 years). Areas with higher poverty levels, crowding, and lower education levels accounted for disproportionately higher proportions of hemodialysis-associated S. aureus bloodstream infections.Disparities exist in hemodialysis-associated S. aureus infections. Health care providers and public health professionals should prioritize prevention and optimized treatment of ESKD, identify and address barriers to lower-risk vascular access placement, and implement established best practices to prevent bloodstream infections.

BACKGROUND:The microbiologic etiologies, clinical manifestations, and antimicrobial treatment of neonatal infections differ substantially from infections in adult and pediatric patient populations. In 2019, the Centers for Disease Control and Prevention developed neonatal-specific (Standardized Antimicrobial Administration Ratios SAARs), a set of risk-adjusted antimicrobial use metrics that hospitals participating in the National Healthcare Safety Network's (NHSN's) antimicrobial use surveillance can use in their antibiotic stewardship programs (ASPs).METHODS:The Centers for Disease Control and Prevention, in collaboration with the Vermont Oxford Network, identified eligible patient care locations, defined SAAR agent categories, and implemented neonatal-specific NHSN Annual Hospital Survey questions to gather hospital-level data necessary for risk adjustment. SAAR predictive models were developed using 2018 data reported to NHSN from eligible neonatal units.RESULTS:The 2018 baseline neonatal SAAR models were developed for 7 SAAR antimicrobial agent categories using data reported from 324 neonatal units in 304 unique hospitals. Final models were used to calculate predicted antimicrobial days, the SAAR denominator, for level II neonatal special care nurseries and level II/III, III, and IV NICUs.CONCLUSIONS:NHSN's initial set of neonatal SAARs provides a way for hospital ASPs to assess whether antimicrobial agents in their facility are used at significantly higher or lower rates compared with a national baseline or whether an individual SAAR value is above or below a specific percentile on a given SAAR distribution, which can prompt investigations into prescribing practices and inform ASP interventions.

Objective: To evaluate hospital-level variation in using first-line antibiotics for Clostridioides difficile infection (CDI) based on the burden of laboratory-identified (LabID) CDI. Methods: Using data on hospital-level LabID CDI events and antimicrobial use (AU) for CDI (oral/rectal vancomycin or fidaxomicin) submitted to the National Healthcare Safety Network in 2019, we assessed the association between hospital-level CDI prevalence (per 100 patient admissions) and rate of CDI AU (days of therapy per 1,000 days present) to generate a predicted value of AU based on CDI prevalence and CDI test type using negative binomial regression. The ratio of the observed to predicted AU was then used to identify hospitals with extreme discordance between CDI prevalence and CDI AU, defined as hospitals with a ratio outside of the intervigintile range. Results: Among 963 acute-care hospitals, rate of CDI prevalence demonstrated a positive dose-response relationship with rate of CDI AU. Compared with hospitals without extreme discordance (n = 902), hospitals with lower-than-expected CDI AU (n = 31) had, on average, fewer beds (median, 106 vs 208), shorter length of stay (median, 3.8 vs 4.2 days), and higher proportion of undergraduate or nonteaching medical school affiliation (48% vs 39%). Hospitals with higher-than-expected CDI AU (n = 30) were similar overall to hospitals without extreme discordance. Conclusions: The prevalence rate of LabID CDI had a significant dose-response association with first-line antibiotics for treating CDI. We identified hospitals with extreme discordance between CDI prevalence and CDI AU, highlighting potential opportunities for data validation and improvements in diagnostic and treatment practices for CDI.

Background: The emergence and spread of drug-resistant pathogens continues to significantly impact patient safety and healthcare systems. Although antimicrobial susceptibility test (AST) results of clinical specimens are used by individual facilities for antimicrobial resistance surveillance, accurate tracking and benchmark comparison of a facility’s antimicrobial resistance using national data requires risk-adjusted methods to be more meaningful. The CDC NHSN Antimicrobial Resistance (AR) Option collects patient-level, deduplicated, isolate information, including AST results, for >20 organisms from cerebrospinal fluid, lower respiratory tract (LRT), blood, and urinary specimens. To provide risk-adjusted national benchmarks, we developed prediction models for incidence of hospital-onset isolates with antimicrobial resistance. Methods: We analyzed AST results of isolates reported through the NHSN AR Option for January through December 2019. Isolates from facilities that had >10% missing AST results for the organism-drug combinations or from hospitals that used outdated breakpoints were excluded. We assessed associations between facility-level factors and incidence rates of hospital-onset (specimen collected 3 days or more after hospital admission) isolates of specific drug-resistant phenotypes from blood, LRT, and urinary specimens. Factors included number of beds, length of stay, and prevalence of community onset isolates of the same phenotype. Drug-resistant phenotypes assessed included methicillin-resistant Staphylococcus aureus (MRSA), multidrug-resistant (MDR) Pseudomonas aeruginosa, carbapenem-resistant Enterobacterales (CRE), fluoroquinolone-resistant Pseudomonas aeruginosa, fluoroquinolone-resistant Enterobacterales, and extended-spectrum cephalosporin-resistant Enterobacterales. Isolates of different phenotypes and from different specimen sources were modeled separately. Negative binomial regression was used to evaluate the factors associated with antimicrobial resistance incidence. Variable entry into the models is based on significance level P Among the models, 1 for each drug-resistant phenotype-specimen type combination, the number of isolates with AST results ranged from 718 (Pseudomonas aeruginosa–fluoroquinolones, blood) to 16,412 (Enterobacterales–fluoroquinolones, urine). The pooled incidence rate was highest for fluoroquinolone-resistant Enterobacterales in urinary specimens (0.2179 isolates per 1,000 patient days) among all phenotype-specimen combinations evaluated (Table 1). The incidence of drug-resistant isolates was consistently associated with community-onset prevalence across models evaluated. Other associated factors varied across phenotype-specimen combinations (Table 2). Conclusions: We developed statistical models to predict facility-level incidence rates of hospital-onset antimicrobial resistant isolates based on community-onset drug-resistant prevalence and facility characteristics. These models will enable facilities to compare antimicrobial resistance rates to the national benchmarks and therefore to inform their antimicrobial stewardship and infection prevention efforts.Funding: NoneDisclosures: None

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This cross-sectional study evaluates the appropriateness of antimicrobial use for hospitalized patients treated for community-acquired pneumonia or a urinary tract infection present at admission or for patients who had received fluoroquinolone or intravenous vancomycin treatment.

Objective: The rapid spread of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) throughout key regions of the United States in early 2020 placed a premium on timely, national surveillance of hospital patient censuses. To meet that need, the Centers for Disease Control and Prevention's National Healthcare Safety Network (NHSN), the nation's largest hospital surveillance system, launched a module for collecting hospital coronavirus disease 2019 (COVID-19) data. We present time-series estimates of the critical hospital capacity indicators from April 1 to July 14, 2020. Design: From March 27 to July 14, 2020, the NHSN collected daily data on hospital bed occupancy, number of hospitalized patients with COVID-19, and the availability and/or use of mechanical ventilators. Time series were constructed using multiple imputation and survey weighting to allow near-real-time daily national and state estimates to be computed. Results: During the pandemic's April peak in the United States, among an estimated 431,000 total inpatients, 84,000 (19%) had COVID-19. Although the number of inpatients with COVID-19 decreased from April to July, the proportion of occupied inpatient beds increased steadily. COVID-19 hospitalizations increased from mid-June in the South and Southwest regions after stay-at-home restrictions were eased. The proportion of inpatients with COVID-19 on ventilators decreased from April to July. Conclusions: The NHSN hospital capacity estimates served as important, near-real-time indicators of the pandemic's magnitude, spread, and impact, providing quantitative guidance for the public health response. Use of the estimates detected the rise of hospitalizations in specific geographic regions in June after they declined from a peak in April. Patient outcomes appeared to improve from early April to mid-July.

BACKGROUND:In the 2011 US hospital prevalence survey of healthcare-associated infections and antimicrobial use 50% of patients received antimicrobial medications on the survey date or day before. More hospitals have since established antimicrobial stewardship programs. We repeated the survey in 2015 to determine antimicrobial use prevalence and describe changes since 2011. METHODS:The Centers for Disease Control and Prevention's Emerging Infections Program sites in 10 states each recruited ≤25 general and women's and children's hospitals. Hospitals selected a survey date from May-September 2015. Medical records for a random patient sample on the survey date were reviewed to collect data on antimicrobial medications administered on the survey date or day before. Percentages of patients on antimicrobial medications were compared; multivariable log-binomial regression modeling was used to evaluate factors associated with antimicrobial use. RESULTS:Of 12 299 patients in 199 hospitals, 6084 (49.5%; 95% CI, 48.6-50.4%) received antimicrobials. Among 148 hospitals in both surveys, overall antimicrobial use prevalence was similar in 2011 and 2015, although the percentage of neonatal critical care patients on antimicrobials was lower in 2015 (22.8% vs 32.0% [2011]; P = .006). Fluoroquinolone use was lower in 2015 (10.1% of patients vs 11.9% [2011]; P < .001). Third- or fourth-generation cephalosporin use was higher (12.2% vs 10.7% [2011]; P = .002), as was carbapenem use (3.7% vs 2.7% [2011]; P < .001). CONCLUSIONS:Overall hospital antimicrobial use prevalence was not different in 2011 and 2015; however, differences observed in selected patient or antimicrobial groups may provide evidence of stewardship impact.

BACKGROUND:The Standardized Antimicrobial Administration Ratio (SAAR) is a risk-adjusted metric of antimicrobial use (AU) developed by the Centers for Disease Control and Prevention (CDC) in 2015 as a tool for hospital antimicrobial stewardship programs (ASPs) to track and compare AU with a national benchmark. In 2018, CDC updated the SAAR by expanding the locations and antimicrobial categories for which SAARs can be calculated and by modeling adult and pediatric locations separately. METHODS:We identified eligible patient-care locations and defined SAAR antimicrobial categories. Predictive models were developed for eligible adult and pediatric patient-care locations using negative binomial regression applied to nationally aggregated AU data from locations reporting ≥9 months of 2017 data to the National Healthcare Safety Network (NHSN). RESULTS:2017 Baseline SAAR models were developed for 7 adult and 8 pediatric SAAR antimicrobial categories using data reported from 2156 adult and 170 pediatric locations across 457 hospitals. The inclusion of step-down units and general hematology-oncology units in adult 2017 baseline SAAR models and the addition of SAARs for narrow-spectrum B-lactam agents, antifungals predominantly used for invasive candidiasis, antibacterial agents posing the highest risk for Clostridioides difficile infection, and azithromycin (pediatrics only) expand the role SAARs can play in ASP efforts. Final risk-adjusted models are used to calculate predicted antimicrobial days, the denominator of the SAAR, for 40 SAAR types displayed in NHSN. CONCLUSIONS:SAARs can be used as a metric to prompt investigation into potential overuse or underuse of antimicrobials and to evaluate the effectiveness of ASP interventions.

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: NoneDisclosures: 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

Abstract Background Clostridioides difficile infections (CDIs) are an urgent public health threat, accounting for 223,900 infections and 12,800 deaths in hospitalized patients annually. In early 2018, the Infectious Disease Society of America (IDSA) recommended oral vancomycin or fidaxomicin as the first-line antibiotics for CDIs. To track the uptake of IDSA’s recommendations, we evaluated the association between CDI prevalence and use of first-line antibiotics in hospitals reporting to the Centers for Disease Control and Prevention’s (CDC’s) National Healthcare Safety Network (NHSN). Methods We matched 2018 hospital-level, NHSN data on laboratory-identified CDIs with NHSN antimicrobial use (AU) data for the same time period. Hospitals that submitted < 6 months of either data type in 2018 were excluded. The association between quarterly hospital-level CDI prevalence rates per 100 patient-admissions and use of CDI antibiotics (oral vancomycin plus fidaxomicin) per 1,000 days-present was evaluated using Pearson’s linear correlation coefficient and using Goodman and Kruskal’s gamma (G) on ordinal quartiles to assess rates of discordant pairs. Results Among the 2735 hospital-level quarters based on 714 hospitals included in the study, CDI prevalence (median: 0.46 per 100 patient-admissions) and CDI antibiotic use (median: 8.85 antibiotic-days per 1,000 days-present) demonstrated only a moderately positive correlation (r = 0.48). Among hospitals in the highest quartile for CDI prevalence, 5.1% were in the lowest quartile for antibiotic use. Among hospitals in the highest quartile for antibiotic use, 5.3% were in the lowest quartile for CDI prevalence, and 54.2% were in the highest quartile for CDI prevalence (G = 0.60; 95% CI: 0.57–0.63). Correlation of hospital-level Clostridioides difficile infection (CDI) prevalence rates and oral vancomycin and fidaxomicin use in U.S. acute care hospitals, 2018 Distribution of hospital-level Clostridioides difficile infection (CDI) prevalence rates and oral vancomycin and fidaxomicin use in ordinal quartiles (Q1–Q4) to access rates of discordant pairs Conclusion The moderate correlation and discordant rates suggest that vancomycin and fidaxomicin are less frequently used as primary antibiotics in some hospitals; whereas in others, CDI antibiotic use is occurring in the absence of positive laboratory tests for CDI. To further investigate this discordance, there is a need to assess hospitals’ prescribing and testing practices in an ongoing manner. These findings may be useful to serve as baseline for measuring progress of appropriateness of treatment and testing for CDIs. Disclosures All Authors: No reported disclosures

BACKGROUNDThe Antimicrobial Use (AU) Option of the Centers for Disease Control and Prevention's National Healthcare Safety Network (NHSN) is a surveillance resource that can provide actionable data for antibiotic stewardship programs. Such data are used to enable measurements of AU across hospitals and before, during, and after stewardship interventions.METHODSWe used monthly AU data and annual facility survey data submitted to the NHSN to describe hospitals and neonatal patient care locations reporting to the AU Option in 2017, examine frequencies of most commonly reported agents, and analyze variability in AU rates across hospitals and levels of care. We used results from these analyses in a collaborative project with Vermont Oxford Network to develop neonatal-specific Standardized Antimicrobial Administration Ratio (SAAR) agent categories and neonatal-specific NHSN Annual Hospital Survey questions.RESULTSAs of April 1, 2018, 351 US hospitals had submitted data to the AU Option from at least 1 neonatal unit. In 2017, ampicillin and gentamicin were the most frequently reported antimicrobial agents. On average, total rates of AU were highest in level III NICUs, followed by special care nurseries, level II-III NICUs, and well newborn nurseries. Seven antimicrobial categories for neonatal SAARs were created, and 6 annual hospital survey questions were developed.CONCLUSIONSA small but growing percentage of US hospitals have submitted AU data from neonatal patient care locations to NHSN, enabling the use of AU data aggregated by NHSN as benchmarks for neonatal antimicrobial stewardship programs and further development of the SAAR summary measure for neonatal AU.

Abstract Background Improving antimicrobial use is a key component of controlling antimicrobial resistance. Multiple factors influence inpatient provider antimicrobial prescribing decisions, making it challenging to develop standard methods to evaluate prescribing quality in hospitals. In 2015, CDC’s Emerging Infections Program (EIP) conducted a hospital antimicrobial use prevalence survey and collected data to assess prescribing quality in selected scenarios, including fluoroquinolone (FQ) treatment. Methods EIP sites (CA, CO, CT, GA, MD, MN, NM, NY, OR, TN) each recruited up to 25 hospitals for the survey. Each hospital selected a survey date during May–September 2015. Among randomly selected inpatients on the survey date, EIP staff identified those ≥18 years old who received FQ treatment on the survey date or the day prior and reviewed medical records to gather data on underlying conditions, infections, and diagnostic tests. We used these data to update a previously developed prescribing quality assessment pathway that categorized FQ treatment as supported or unsupported based on medical record documentation. Results Among 12,299 patients in 199 hospitals, 1084 (8.7%) received FQ treatment; 756 (70%) were treated for a single infection type during their hospitalization and were ≥18 years old. The pathway categorized FQ treatment as supported for 646 (85.4%) and unsupported for 110 patients (14.6%) (figure). Almost half of unsupported treatment was due to a lack of compatible signs or symptoms of infection in a patient from whom an organism susceptible or likely susceptible to an FQ was identified from a nonsterile site (49/110 patients, 44.5%), suggesting colonization. Conclusion Utilization of a pathway that incorporates detailed clinical data enabled us to apply a standard approach to assess FQ prescribing quality in hospitals. A high percentage of FQ treatment was supported, possibly reflecting efforts in recent years to reduce inappropriate use. Our assessment approach also identified opportunities for further improvements in inpatient FQ stewardship. Incorporation of additional elements in the pathway, such as the availability of other antibiotic choices in clinical scenarios where FQ use is currently supported (e.g., pneumonia) could further enhance the pathway’s performance. Disclosures All authors: No reported disclosures.

Background. To provide a standardized, risk-adjusted method for summarizing antibiotic use (AU), enable hospitals to track their AU over time and compare their AU data to national benchmarks, the Centers for Disease Control and Prevention developed the Standardized Antimicrobial Administration Ratio (SAAR). Methods. Hospitals reporting to the National Healthcare Safety Network (NHSN) AU Option collect and submit aggregated AU data electronically as antimicrobial days of therapy per patient days present. SAARs were developed for specific NHSN adult and pediatric patient care locations and cover five antimicrobial agent categories: (1) broad-spectrum agents predominantly used for hospital-onset/multi-drug resistant bacteria; (2) broad-spectrum agents predominantly used for community-acquired infections; (3) anti-methicillin-resistant Staphylococcus aureus agents; (4) agents predominantly used for surgical site infection prophylaxis; and (5) all antibiotic agents. The SAAR is an observed-to-predicted use ratio where predicted use is estimated from a statistical model; a SAAR of 1 indicates that observed use and predicted use are equal. Results. Most location-level SAARs were statistically significantly different than 1: adult locations up to 52% lower than 1 and up to 41% higher than 1. Median SAARs in adult and pediatric ICUs had a range of 0.667-1.119. SAAR distributions serve as an external comparison to national SAARs. Conclusions. This is the first aggregate AU metric that uses point-of-care, antimicrobial administration data electronically reported to a national surveillance system to enable risk-adjusted, AU comparisons across multiple hospitals. Endorsed by the National Quality Forum, SAARs provide AU benchmarks that stewardship programs can use to help drive improvements.

BACKGROUND A point-prevalence survey that was conducted in the United States in 2011 showed that 4% of hospitalized patients had a health care-associated infection. We repeated the survey in 2015 to assess changes in the prevalence of health care-associated infections during a period of national attention to the prevention of such infections. METHODS At Emerging Infections Program sites in 10 states, we recruited up to 25 hospitals in each site area, prioritizing hospitals that had participated in the 2011 survey. Each hospital selected 1 day on which a random sample of patients was identified for assessment. Trained staff reviewed medical records using the 2011 definitions of health care-associated infections. We compared the percentages of patients with health care-associated infections and performed multivariable log-binomial regression modeling to evaluate the association of survey year with the risk of health care-associated infections. RESULTS In 2015, a total of 12,299 patients in 199 hospitals were surveyed, as compared with 11,282 patients in 183 hospitals in 2011. Fewer patients had health care-associated infections in 2015 (394 patients [3.2%; 95% confidence interval {CI}, 2.9 to 3.5]) than in 2011 (452 [4.0%; 95% CI, 3.7 to 4.4]) (P<0.001), largely owing to reductions in the prevalence of surgical-site and urinary tract infections. Pneumonia, gastrointestinal infections (most of which were due to Clostridium difficile [now Clostridioides difficile]), and surgical-site infections were the most common health care-associated infections. Patients' risk of having a health care-associated infection was 16% lower in 2015 than in 2011 (risk ratio, 0.84; 95% CI, 0.74 to 0.95; P = 0.005), after adjustment for age, presence of devices, days from admission to survey, and status of being in a large hospital. CONCLUSIONS The prevalence of health care-associated infections was lower in 2015 than in 2011. To continue to make progress in the prevention of such infections, prevention strategies against C. difficile infection and pneumonia should be augmented. (Funded by the Centers for Disease Control and Prevention.)

Vancomycin is the most common antimicrobial drug administered to hospitalized patients, including children >90 days old, although the prevalence of β-lactam antibiotic resistance among Gram-positive pathogens is relatively low in children. Reducing inappropriate vancomycin use in children can reduce harm from antibiotic-associated adverse events and antimicrobial resistance (AR). We developed an approach to evaluating pediatric intravenous (IV) vancomycin prescribing quality using medical record data. Hospitals in three Emerging Infections Program (EIP) sites (CA, NM, and TN) were recruited to participate. Patients <18 years who received IV vancomycin in 2013 were identified through pharmacy records, excluding those on IV vancomycin solely for surgical prophylaxis. Trained EIP staff collected medical record data. We created a prescribing quality evaluation pathway using data on infection type, signs, symptoms, penicillin allergy, and AR risk factors. Clinically supported prescribing events were those with a positive culture for a Gram-positive organism with β-lactam resistance or unknown susceptibility; severe penicillin allergy; bone, joint, skin/soft tissue or central nervous system infection; pneumonia with AR risk factors; or events where vancomycin was stopped within 1 day of culture results for an oxacillin or penicillin/ampicillin-susceptible organism. Sixty-five patients in 12 hospitals were evaluated. The median age was 7 years (interquartile range [IQR] 4–14), and median hospital stay was 7 days (IQR 3–16). The median vancomycin treatment length was 3 days (IQR 2–6); 41 patients (63%) received ≥3 days. Vancomycin use was clinically supported in 47 patients (72%) and unsupported in 18 (28%) (figure). Most unsupported use was for infections lacking microbiology data and for which vancomycin would not usually be indicated, such as pneumonia without AR risk factors (9/18, 50%). The use of IV vancomycin was not supported for >25% of children, indicating opportunities to improve prescribing and reduce unnecessary vancomycin use. Further analysis will utilize this prescribing pathway to evaluate the most recent prevalence survey data to identify areas to target stewardship interventions. All authors: No reported disclosures.