Abstract
BackgroundUnderstanding antimicrobial consumption is essential to mitigate the development of antimicrobial resistance, yet robust data in children are sparse and methodologically limited. Electronic prescribing systems provide an important opportunity to analyse and report antimicrobial consumption in detail.ObjectivesWe investigated the value of electronic prescribing data from a tertiary children’s hospital to report temporal trends in antimicrobial consumption in hospitalized children and compare commonly used metrics of antimicrobial consumption.MethodsDaily measures of antimicrobial consumption [days of therapy (DOT) and DDDs] were derived from the electronic prescribing system between 2010 and 2018. Autoregressive moving-average models were used to infer trends and the estimates were compared with simulated point prevalence surveys (PPSs).ResultsMore than 1.3 million antimicrobial administrations were analysed. There was significant daily and seasonal variation in overall consumption, which reduced annually by 1.77% (95% CI 0.50% to 3.02%). Relative consumption of meropenem decreased by 6.6% annually (95% CI −3.5% to 15.8%) following the expansion of the hospital antimicrobial stewardship programme. DOT and DDDs exhibited similar trends for most antimicrobials, though inconsistencies were observed where changes to dosage guidelines altered consumption calculation by DDDs, but not DOT. PPS simulations resulted in estimates of change over time, which converged on the model estimates, but with much less precision.ConclusionsElectronic prescribing systems offer significant opportunities to better understand and report antimicrobial consumption in children. This approach to modelling administration data overcomes the limitations of using interval data and dispensary data. It provides substantially more detailed inferences on prescribing patterns and the potential impact of stewardship interventions.
Highlights
Antimicrobial resistance (AMR) represents a significant and growing threat to public health
This study aimed to model antimicrobial consumption in children admitted to Great Ormond Street Hospital for Children (GOSH) in order to observe seasonal and temporal variation, compare day(s) on therapy’ (DOT) with DDDs, compare the utility of continuous estimates with the established point prevalence survey (PPS) methodology and report prescribing quality estimates using the recently published England-adapted ‘Access, Watch and Reserve’ (AWaRe) index.[7]
Polynomial terms were tested in the regression models where generalized additive model (GAM) plots suggested a non-linear relationship, and were retained where their inclusion improved the fit of the model to the data
Summary
Antimicrobial resistance (AMR) represents a significant and growing threat to public health. A central element of these is the strengthening of capacity to carry out surveillance of both antimicrobial consumption and resistance.[1,2] In 2017, The National Health Service England (NHSE) Commissioning for Quality and Innovation for Antimicrobial Resistance (CQUIN AMR) guidance tasked institutions with reducing total antimicrobial prescribing. Understanding antimicrobial consumption is essential to mitigate the development of antimicrobial resistance, yet robust data in children are sparse and methodologically limited. Electronic prescribing systems provide an important opportunity to analyse and report antimicrobial consumption in detail
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