Goal

With 70–80% of antibiotics consumed in primary healthcare, optimising prescribing in this setting is crucial. Achieving this requires a better understanding of the relationship between prescribing levels for common infections and the risk of subsequent adverse outcomes. This work aims to improve understanding of antibiotic prescribing for 17 common infections by examining prescribing patterns, variability, drivers, and the associations between prescribing levels and patient outcomes.  

Lead

Nam Nguyen – Nuffield Department of Primary Care Health Science, University of Oxford

What we did

This study uses the Clinical Practice Research Datalink (CPRD), a dataset that collects patient-level primary healthcare data from a network of GP practices across the UK. The infections of interest include acute bronchitis, cough, acute otitis media, acute rhinosinusitis, acute sore throat, asthma exacerbation, COPD exacerbation, acute gastroenteritis, impetigo, any lower or upper respiratory tract infection, and urinary tract infection. The antibiotic prescribing decisions assessed include whether an antibiotic was issued, the type of antibiotic prescribed, and the duration of treatment. A total of 25,338,320 visits for common infections were included in our study. These visits took place between 2016 and 2019 and involved 9,444,048 patients across 1,494 general practices in the UK. 

Key learnings

The results of this project will provide valuable insights into antibiotic prescribing in primary healthcare, which may help inform targets for antibiotic stewardship interventions in the studied country. Importantly, by developing the analytical approach within a robust and comprehensive dataset, the study also lays the foundation for a framework that can be applied in other settings where patient-level primary healthcare data are available at a local or national level. 

Outputs

TBC

Funder

The Wellcome Trust