How should we tackle antimicrobial resistance in primary care? Lessons from infections research
The ninth in our series of webinars focusing on innovation and impact in primary care research.
Date: 16 January 2025, 1-2pm, via Zoom.
Contributors:
- Alastair Hay, Professor of Primary Care, Centre for Academic Primary Care, University of Bristol
- Emily Brown, Clinical Research Fellow, Centre for Academic Primary Care, University of Bristol
- Christie Cabral, Senior Lecturer, Centre for Academic Primary Care, University of Bristol
- Polly Duncan, Clinical Research Fellow, Centre for Academic Primary Care, University of Bristol
- Ioana Fodor, Senior Research Projects Manager, Centre for Academic Primary Care, University of Bristol
- Ashley Hammond, Research Fellow, Centre for Academic Primary Care, University of Bristol
Download the PowerPoint slides: How should we tackle antimicrobial resistance in primary care? (PDF, 4,210kB)
Watch the recording:
Description
We all experience infections. They are the most common reason people request an appointment with their GP. This often leads to antibiotics being prescribed. In fact, over 80% of health service antibiotics are prescribed by in primary care. Many of these prescriptions are unnecessary and contribute to antimicrobial resistance (AMR), which causes 30,000 deaths in the UK and Europe annually and is now considered one of the greatest threats to public health globally.
In this webinar, members of the Centre for Academic Primary Care’s Infections Research team ask: what should we do about it?
Drawing on their pioneering research, which has demonstrated how inappropriate antibiotic prescribing in primary care makes AMR worse, the team will share findings that offer some of the answers. This will include discussion of findings from a variety of studies looking at different aspects of the problem, including: mechanisms of infection transmission; approaches to self-care; delayed antibiotic prescribing; and research looking at the feasibility and efficacy of rapid tests that help clinicians quickly identify whether an infection is treatable with antibiotics or not.
