Longitudinal point prevalence survey of antibacterial use in Northern Ireland using the European Surveillance of Antimicrobial Consumption (ESAC) PPS and Global-PPS tool.
G M Al-TaaniM ScottD FarrenF GilmoreB MccullaghC HibberdA MccorryA VersportenH GoossensP ZarbMamoon A AldeyabPublished in: Epidemiology and infection (2018)
Antimicrobial resistance is a limiting factor for the success of the treatment of infectious diseases and is associated with increased morbidity and cost. The present study aims to evaluate prescribing patterns of antimicrobials and quantify progress in relation to targets for quality improvement in the prescription of antimicrobials in Northern Ireland's secondary care sector using three repetitive point prevalence surveys (PPS) over a 6-year period: the European Surveillance of Antimicrobial Consumption (ESAC-PPS) in 2009 and 2011 and the Global-PPS on Antimicrobial Consumption and Resistance in 2015. Out of 3605 patients surveyed over the three time points, 1239 (34.4%) were treated with an antibiotic, the most frequently prescribed antibiotic groups were a combination of penicillins, including β-lactamase inhibitors. Compliance with hospital antibiotic policies in 2009, 2011 and 2015 were 54.5%, 71.5% and 79.9%, respectively. Likewise, an indication for treatment was recorded in patient notes 88.5%, 87.7% and 90.6% in 2009, 2011 and 2015, respectively, and surgical prophylactic antibiotic prescriptions for >24 h was 3.9%, 3.2% and 0.7% in 2009, 2011 and 2015, respectively. Treatment based on biomarker data was used in 61.5% of cases. In conclusion, a general trend in the improvement of key antimicrobial-related quality indicators was noted. The PPS tool provided a convenient, inexpensive surveillance system of antimicrobial consumption and should be considered an essential component to establish and maintain informed antibiotic stewardship in hospitals.
Keyphrases
- staphylococcus aureus
- quality improvement
- public health
- healthcare
- antimicrobial resistance
- infectious diseases
- primary care
- risk factors
- newly diagnosed
- machine learning
- palliative care
- escherichia coli
- emergency department
- high frequency
- combination therapy
- chronic pain
- prognostic factors
- health insurance
- replacement therapy
- data analysis