BRIT – Using data to tackle antibiotic resistance

Manchester icon Greater Manchester

Researchers involved: Tjeerd van Staa, Benjamin Brown, Anna Molter, Miguel Belmonte, Victoria Palin, Chirag Mistry, Edd Tempest
Disease area impacted: Infectious diseases
Key partners NHS and Public Health England

Project Overview

Antibiotics are used to kill bacteria when we get an infection or to protect us when our immune systems are vulnerable. At the moment we are facing a crisis in public health.  The bacteria are becoming more resistant to the antibiotics and as a result they are becoming less effective, in the future there’s a chance they might stop working altogether.

One of the reasons for this is over-prescription.  Antibiotics are being given out too often and the bacteria are becoming immune to them.  This project, delivered by the Greater Manchester CHC is applying a tech savvy solution to help understand and tackle the problem.

By making better use of health data and presenting results in a more powerful way, researchers at GM CHC are working to promote a better understanding of the key factors which influence antibiotic prescribing.

The BRIT team have worked with anonymous GP records, A&E departments and out-of-hours clinics, to understand which services are prescribing the most antibiotics. To promote better understanding of the drivers which impact antibiotic prescribing, the research team have developed two data dashboards:

National Antibiotic Prescribing Dashboard

The GM CHC team have developed a National Antibiotic Prescribing Dashboard which allows a range of health stakeholders, including policy makers, to better understand the factors that influence the UK’s antibiotic prescribing profile.

The National Antibiotic Prescribing Dashboard data shows that factors such as GP Practice location, time spent with patients and staff shortages impact on the number of antibiotics prescribed. The data shows that antibiotics are more likely to be prescribed in busy, northern GP practices. The dashboard also reveals that patients considered to be at ‘low risk’ of hospitalisation from infection-related complications are prescribed just as many antibiotics as patients who are at ‘high risk’ of being hospitalised within the next 30 days.

Accessing the National Antibiotic Prescribing Dashboard

To access the National Antibiotic Prescribing Dashboard, visit

GP Antibiotic Prescribing Dashboard

The GP dashboard uses anonymised health data to allow GPs and healthcare professionals to compare their own antibiotic prescribing patterns with national and regional figures. Health care practitioners are also able to identify patients considered to be at high-risk of developing infection related complications, helping decisions on whether or not an antibiotic prescription is needed.

The data driven insights also show which antibiotics are being issued for common infections, and the proportion of these prescriptions that deviate from the recommended guidelines, allowing users to track practice improvements over time.

It’s currently being used by 22 practices across Greater Manchester.

What the GM CHC research team said about the Antibiotic Prescribing Dashboard

Dr Miguel Belmonte:

“Antibiotic prescribing is influenced by a wide variety of different factors such as number of registered patients and number of general practitioners per practice to deal with volume of consultations. We summarise information contained in electronic health records to aid understanding of the UK’s antibiotic prescribing landscape. Our aim with this dashboard is to feedback actionable information to healthcare professionals in order to optimise antibiotic prescribing and shape future antibiotic policy recommendations.”

Dr Victoria Palin:
“Dashboard users have insight to the antibiotics are being prescribed for common infections, and what proportion of these prescriptions deviate from the recommended guidelines. One feature the dashboard highlights is the enormous prescribing variability for common infections, whilst another feature demonstrates antibiotic prescribing patterns in relation to a patient’s risk of infection related complications. To empower the healthcare sector, the dashboard is ever-evolving and can be tailored to meet the needs of the end user to optimise prescribing.”


1. What data are you using? Are the data anonymised?

De-identified GP records, A&E departments and out-of-hours clinics. All data are anonymised. We will work with the clinical care teams of the patients but the researchers will never have access to patients’ names or addresses.

2. What methods are you using to conduct this work? (How are you using the data?)

This study is observational, we analyse the data as collected by the clinical care teams during routine care and as recorded in the electronic care records used by them. We will analyse the data estimating, for example, the number of patients who are admitted to the hospital for lung infection per 1000 patients.

3. Who will/could benefit? (What will we know that we don’t already?)

The direct benefit will be the NHS, the clinical care teams, the NHS groups that support the clinicians in their prescribing and Public Health England that monitors resistance to antibiotics. Also, our aim is also that future patients will benefit by reducing antibiotic use in patients who have a viral infection (antibiotics do not work in these patients) and by increasing their use in patients at risk of being admitted to hospital for lung infection.

4. What will be the intended outcome of your research project?

The intended outcome is to provide the NHS and clinical care teams with better information on what is happening and who is getting antibiotics and whether the use of antibiotics is reasonable given local resistance patterns to antibiotics.

5. Are there any findings or indications you can report? Are there any publications?

Research outputs include:

Along with publications from the BRIT team: