OBJECTIVE To describe antimicrobial resistance patterns for healthcare-associated infections (HAIs) that occurred in 2011-2014 and were reported to the Centers for Disease Control and Prevention's National Healthcare Safety Network. METHODS Data from central line-associated bloodstream infections, catheter-associated urinary tract infections, ventilator-associated pneumonias, and surgical site infections were analyzed. These HAIs were reported from acute care hospitals, long-term acute care hospitals, and inpatient rehabilitation facilities. Pooled mean proportions of pathogens that tested resistant (or nonsusceptible) to selected antimicrobials were calculated by year and HAI type. RESULTS Overall, 4,515 hospitals reported that at least 1 HAI occurred in 2011-2014. There were 408,151 pathogens from 365,490 HAIs reported to the National Healthcare Safety Network, most of which were reported from acute care hospitals with greater than 200 beds. Fifteen pathogen groups accounted for 87% of reported pathogens; the most common included Escherichia coli (15%), Staphylococcus aureus (12%), Klebsiella species (8%), and coagulase-negative staphylococci (8%). In general, the proportion of isolates with common resistance phenotypes was higher among device-associated HAIs compared with surgical site infections. Although the percent resistance for most phenotypes was similar to earlier reports, an increase in the magnitude of the resistance percentages among E. coli pathogens was noted, especially related to fluoroquinolone resistance. CONCLUSION This report represents a national summary of antimicrobial resistance among select HAIs and phenotypes. The distribution of frequent pathogens and some resistance patterns appear to have changed from 2009-2010, highlighting the need for continual, careful monitoring of these data across the spectrum of HAI types. Infect Control Hosp Epidemiol 2016;1-14.

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.

Case reports Case I-A 73 year old man, admitted because of palpitations, was started on 1 Knyvett AF. The pulmonary lesions of chickenpox. QJMed 1966;139:313-23. 2 Bocles JS, Ehrenkranz NJ, Marks A. Abnormalities ofrespiratory function in varicella pneumonia.

Background The Standardized Antimicrobial Administration Ratio (SAAR) is a risk-adjusted metric of antimicrobial use (AU) developed by the CDC in 2015 as a tool for hospital antimicrobial stewardship programs (ASPs) to track and compare AU to 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 seven adult and eight pediatric SAAR antimicrobial categories using data reported from 2,156 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 beta-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.