The more widely that antibiotics are used, the more likely bacteria are to become resistant to them. NHS general practices (GP) are responsible for the majority of the antibiotics prescribed in the community. There is evidence that prescribing antibiotics is not always necessary, for some conditions a patient's recovery time with or without antibiotics is similar and therefore antibiotic prescribing is often inappropriate. To counteract the increase in resistance to antibiotics seen, new antibiotic prescribing targets have been published to encourage general practices to reduce antibiotic prescribing. Where a treatment is required for a bacterial infection and the treatment time is delayed, or where treatment is not provided, a more severe infection may develop as a consequence. A more serious infection, including infections of the blood, would increase a patient's risk of severe illness and death. The purpose of this study is to use routinely collected data from a sample of GPs and hospitals across England, to investigate the effect of a national intervention (introduced to reduce antibiotic prescribing) on levels of primary care prescribing and the associated unintended health outcomes that may occur consequently. Findings from this study would contribute to wider evaluation of the quality premium/policy change.
Antibiotics differ to other medical drugs, as their overuse and misuse selects resistance and weakens their effectiveness. The threat of antimicrobial resistance has been of growing public health concern, with the apprehension that many common and serious infections will become increasingly difficult to treat, if not entirely untreatable with pan-resistant infections. In response to the increase of antimicrobial resistance, quality premiums were introduced to improve antibiotic prescribing. This change should impact and reduce unnecessary antibiotic exposure, with the intention of easing or slowing the rate of resistance. A reduction in overall antimicrobial prescribing however, may be accompanied with a reduction in appropriate therapy. A delay in treatment where antibiotics are required permits bacteria to propagate and may cause more severe infections or other clinical complications, e.g. bacteraemia, death. This study will analyse linked Clinical Practice Research Database (CPRD), Hospital Episode Statistic (HES) and Office for National Statistics (ONS) data to examine a patient's pathway through the healthcare system and distinguish any adverse outcomes related to the introduction of the quality premiums. Time series analysis will be completed to examine changes in the time trends of prescribing antibiotics and adverse outcomes, prior to and following the intervention (i.e. the Quality premium).
Outcomes of interest: 1) Antibiotic prescription rate: Have prescribing practices of antibiotics altered? Has there been a reduction in antibiotic prescribing since the introduction of the quality premiums; assessed by identifying variations in: - Proportion of patients prescribed antibiotics for diagnoses of interest - The number of antibiotic items per STAR-PU (specific therapeutic group age-sex weightings related prescribing units). - Stratifying measures above by total or broad-spectrum antibiotics (co-amoxiclav, cephalosporins, quinolones). 2) Incidence of adverse consequences. Primary and secondary care outcomes have been identified using CPRD and ICD-10 codes. a) Incidence in primary care as well as an increase in severity will be assessed; as indicated by hospital admission (for the same or clinically related condition during 60 days following diagnosis) and mortality (60 day-all cause mortality from initial consultation). b) Count of unintended consequences by month (unrelated to primary consultation) 3) Cohort: Odds ratio between exposed (post-QP) and unexposed (pre-QP) group, for RTI, UTI and SSTI.
Paul Aylin - Chief Investigator - Imperial College London
Sabine Bou-Antoun - Corresponding Applicant - Imperial College London
Alan Johnson - Collaborator - Public Health England
Alison Holmes - Collaborator - Imperial College London
Benedict Hayhoe - Collaborator - Imperial College London
Ceire Costelloe - Collaborator - Imperial College London
Myriam Gharbi - Collaborator - Imperial College London
Violeta Balinskaite - Collaborator - Imperial College London
HES Admitted Patient Care;ONS Death Registration Data;Patient Level Index of Multiple Deprivation