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This trial aims to reduce inappropriate prescription of antibiotics and broad spectrum antibiotics by general practitioners (GPs) in England. Unnecessary prescriptions are defined as those that do not improve patient health outcomes. The intervention is to send GPs a letter from the Chief Medical Officer (CMO) that gives feedback on their practice's prescribing levels.
There will be three intervention samples:
Full description
The study will involve three trials, each conducted as non-blinded randomised controlled trial, with GP practices as the unit of randomisation.
Trial 1 Targeting practices whose prescribing in the past year was under the new target but who would exceed the target if they had a 5% increase in prescribing
Trial 2 Targeting practices whose prescribing in the past year was above the new target but who not in the top 20% of prescribers
Trial 3 Targeting practices that are currently in the top 20% of prescribers
Hypotheses: (i) A letter with a social norms message and a specific example of a case where a patient came to harm will be more effective than a feedback letter without a specific example; (ii) A letter telling GPs that they missed the prescribing target will be no less effective than a letter with social norms feedback
For each letter, there will be two versions, one for practices whose prescribing has increased by > 5% in the previous year, informing them of that their prescribing has increased since the previous year, and one for practices whose prescribing has not been increasing.
The letters will signpost GPs to resources to help address patient demand for inappropriate antibiotic prescribing, recognising that many GPs feel that patients expect antibiotics and that GPs may find it difficult to have the necessary patient conversations, especially within a short consultation. As with previous letters, these letters will advise GPs of actions that they can take to reduce inappropriate prescribing, supporting them to have conversations with patients, and there will be TARGET leaflets enclosed.
Power calculation All trials are powered to detect a 2% reduction in prescribing at a significance level of 0.05 with a power of 80%.
Statistical analysis plan In order to test our hypotheses, the investigators will use a fixed effects panel regression model, with time trends accounting for seasonal effects, to estimate the effect of treatment status on prescribing. The investigators will also run ANCOVAs for each month separately and one covering the whole six months of the trial. Analysis will control for baseline prescribing rates and for whether practices got the version of the letter saying that their prescribing has been increasing.
Enrollment
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Inclusion criteria
• GP practices that prescribed more than 0.919 Antibacterial Items/STAR- PU (5% under the target of 0.965) for the twelve months April 2018 - March 2019
Exclusion criteria
• Practices in the 99th percentile of prescribers
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2,963 participants in 8 patient groups
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Data sourced from clinicaltrials.gov
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