Use of the WHO Access, Watch, and Reserve classification to define patterns of hospital antibiotic use (AWaRe): an analysis of paediatric survey data from 56 countries

BACKGROUND: Improving the quality of hospital antibiotic use is a major goal of WHO's global action plan to combat antimicrobial resistance. The WHO Essential Medicines List Access, Watch, and Reserve (AWaRe) classification could facilitate simple stewardship interventions that are widely applicable globally. We aimed to present data on patterns of paediatric AWaRe antibiotic use that could be used for local and national stewardship interventions. METHODS: 1-day point prevalence survey antibiotic prescription data were combined from two independent global networks: the Global Antimicrobial Resistance, Prescribing, and Efficacy in Neonates and Children and the Global Point Prevalence Survey on Antimicrobial Consumption and Resistance networks. We included hospital inpatients aged younger than 19 years receiving at least one antibiotic on the day of the survey. The WHO AWaRe classification was used to describe overall antibiotic use as assessed by the variation between use of Access, Watch, and Reserve antibiotics, for neonates and children and for the commonest clinical indications. FINDINGS: Of the 23 572 patients included from 56 countries, 18 305 were children (77·7%) and 5267 were neonates (22·3%). Access antibiotic use in children ranged from 7·8% (China) to 61·2% (Slovenia) of all antibiotic prescriptions. The use of Watch antibiotics in children was highest in Iran (77·3%) and lowest in Finland (23·0%). In neonates, Access antibiotic use was highest in Singapore (100·0%) and lowest in China (24·2%). Reserve antibiotic use was low in all countries. Major differences in clinical syndrome-specific patterns of AWaRe antibiotic use in lower respiratory tract infection and neonatal sepsis were observed between WHO regions and countries. INTERPRETATION: There is substantial global variation in the proportion of AWaRe antibiotics used in hospitalised neonates and children. The AWaRe classification could potentially be used as a simple traffic light metric of appropriate antibiotic use. Future efforts should focus on developing and evaluating paediatric antibiotic stewardship programmes on the basis of the AWaRe index. FUNDING: GARPEC was funded by the PENTA Foundation. GARPEC-China data collection was funded by the Sanming Project of Medicine in Shenzhen (SZSM2015120330). bioMérieux provided unrestricted funding support for the Global-PPS

An international study of the performance of sample collection from patients

Background and Objectives Collection of a blood sample from the correct patient is the first step in the process of safe transfusion. The aim of this international collaborative study was to assess the frequency of mislabelled and miscollected samples drawn for blood grouping. Materials and Methods Hospitals in 10 countries provided data on sample error rates during a period of at least 3 months, including the last quarter of 2001. Mislabelled samples were defined as those not meeting local criteria for acceptance by the laboratory. Miscollected samples [wrong-blood-in-tube (WBIT)] were defined as samples in which the blood group result differed from the result on file from prior testing. WBIT rates were corrected for the proportion of repeat samples and for undetectable errors occurring as a result of chance collection of blood from the wrong patient with the same ABO group. Participants also completed a questionnaire on current policies regarding sample collection. Results A total of 71 hospitals completed surveys describing policies related to sample collection. Sixty-two hospitals provided usable data on the frequency of mislabelled and miscollected samples. Mislabelled and miscollected samples were common. Based on results from over 690 000 samples, the median hospital performance resulted in a rate for mislabelling of 1 in every 165 samples (6.1 per 1000; interquartile range 1.2-17 per 1000). The presence of national patient identification systems in Sweden and Finland was associated with rates of miscollected samples that were too low to estimate. Outside these nations, miscollected samples demonstrating WBIT occurred at a median rate of 1 in every 1986 samples (0.5 per 1000; interquartile range <0.3-0.9 per 1000). There was great variation worldwide in the reported frequency of mislabelled samples, probably resulting from variation in policies for sample acceptance. Miscollected samples occurred at a more constant rate. Conclusions The rate of mislabelled samples and miscollected samples is 1000-10 000-fold more frequent than the risk of viral infection. Rates of mislabelled samples and WBIT can be tracked as key indicators of performance of an important step in the clinical transfusion process. WBIT episodes represent important 'near-miss' errors. By providing baseline performance data for the collection of patient blood samples, this study may be useful in formulating future national standards of performance for sample collection from patients