Award Title: Cluster randomised trial to improve antibiotic prescribing in primary care: individualised knowledge support during consultation for general practitioners and patients
Funder: Department of Health and Social Care

Abstract: Antibiotics are medicines that are used to prevent and treat bacterial infections. The world urgently needs to change the way it prescribes and uses antibiotics. Without this urgent action, we are heading for a post-antibiotic era, in which antibiotics no longer work (known as antibiotic resistance) and common infections can once again kill. From earlier studies, we have found that general practitioners (GPs) are as likely to give an antibiotic to patients with very low risk as to those with high risks of complications due to infections. Moreover, not every bacterial infection needs to be treated with an antibiotic as most patients get better naturally. In this project, we aim to change the antibiotic prescribing practices of GPs using two methods: (1) by providing advice (“knowledge support”) during consultation on the best approach to treat the patient with an infection; and  (2) by providing regular feedback about their prescribing using  online displays (“dashboards”).. The information given on these dashboards will be based on analyses of anonymised patient records from their GP own practice and will show how their antibiotic prescribing compares to that of other practices. In addition to the dashboards, we will also provide GPs in half of the practices taking part in our project with the knowledge support intervention.. The practices will be selected by flipping a coin (a “cluster randomised trial”). The knowledge support given will consist of a display on the GP’s computer while seeing the ill patient. The GP will need to enter answers to standard questions about the patient’s condition (such as presence of fever). Then, in response, the GP will be presented with feedback on the patient’s risk of complications due to the infection without an antibiotic treatment. This estimate of risk is based on analyses in large national research datasets containing anonymised records of patients with similar conditions. The GP will also receive information about how other GPs would treat similar patients (also known as ‘benchmarking’). The GP will also be able to print out a patient information leaflet that gives personal information about the need of being treated with an antibiotic. For example, a 25-year old patient with a sore throat and minimal symptoms, but otherwise healthy, who is consulting their GP would receive information that the risks of developing complications from not taking antibiotics, although not zero, are very low. This patient information leaflet would also contain information about the risks of taking too many antibiotics and of developing resistance to this antibiotic (so it no longer works for future infections). On the other hand, an elderly patient suffering from multiple diseases would receive information about the importance of taking antibiotics. This approach of giving personalised information is in line with previous studies that showed that patients valued written information that was tailored to their individual circumstances and illness, presenting a balance of harm and benefit related to their treatment. The contents of the patient leaflets will be co-designed with members of the public. The GP will be able to ignore this ‘knowledge support’ or decide not to give the leaflet to the patient. The main outcome of interest is whether this ‘knowledge support’ reduces the overall level of antibiotic prescribing without harming patients by not treating with antibiotics.

Lay Abstract: Antimicrobial resistance is a major threat to public health due to the combination of increasing prevalence of resistant pathogens and diminishing development of new antimicrobial agents. The NHS 2019 Long Term plan states as priority to continue to optimise use, reduce the need for and unintentional exposure to antibiotics. Primary care accounts for 81% of antibiotic prescribing in England. Recent research has found that the likelihood of being treated with antibiotics for a common infection is unrelated to a patient’s risk of infection-related hospital admission. Furthermore, repeated courses of antibiotics, although common practice in primary care, may have limited benefit and be an indicator of adverse outcomes. This project will implement and test a Knowledge Support (KS) infrastructure that provides individualised information to clinician and patient during consultation. This KS would provide real-time, personalised comparative information relevant for the patient’s clinical scenario. By a simply clicking on an icon on their computer screen, clinicians get access to information on “patients like mine” (e.g., the risks of developing clinical complications in similar patients and number-needed-to-treat [NNT] to prevent one hospital admission), tailored recommendations (e.g., best not prescribe amoxicillin given this patient’s frequent prior use), and a patient leaflet that is individualised to the patient. The research question of this project is to evaluate whether individualised KS for General Practitioners (GPs) and patients reduces the level of antibiotic prescribing without increasing the risks of infection-related complications. The KS will be based on the TRANSFoRM infrastructure which activates when the GP enters specific clinical codes into the computer. Symptom information can then be entered along with information on the patient’s medical history and previous antibiotics prescribed. The study design will be a cluster randomised trial comparing two parallel groups of GPs in the UK. In the intervention practices with KS, GPs will be provided with nudging feedback on their individual-level antibiotic` prescribing and their opportunities to improve antibiotic prescribing. The KS activation will be tailored to each individual GP. In collaboration with NICE and Public Health England, this project will develop NNT for infection-related complications and determine possible thresholds for antibiotics across different common infections as well treatment patterns (including incidental and repeated antibiotic use). In addition to NNT, the KS will also provide information on treatment benchmarking (i.e., level of agreement between GPs), which will be developed using the Delphi approach. The personalised patient leaflets will be co-designed with members of the public, including a survey with ranking of different information domains (such as likelihood of the patient developing complications, NNT for antibiotic treatment and possible effects on future resistance). The economic and budget impact of KS will be estimated using incremental cost-effectiveness ratios. A sample size calculation indicates that 124 practices are required (power of 90% for 10% reduction in antibiotic prescribing). This project will implement an exemplar in which insights from advanced analytics of NHS data are made accessible to clinicians and patients when they are making decisions about their care.

Research Activity Codes: 7.3 MANAGEMENT AND DECISION MAKING
Health Categories: GENERIC HEALTH RELEVANCE