Precision antibiotic prescribing using analysed and linked healthcare data

What is the problem?

It can be difficult for clinicians to prescribe the best antibiotics for their patients when they have little information about their patient’s antibiotic history, and their patient’s susceptibility to a certain drug because of their clinical characteristics. This can lead to the prescribing of inappropriate antibiotics and in the long run increase the risk of AMR. Any help and guidance clinicians can get to help them select the best antibiotic will not only benefit their patient but will also help slow down AMR.

What is the solution?

Using linked healthcare data generated from the HDR-UK Southwest Better Care Partnership project, lead investigators Professor Andrew Dowsey (Bristol Medical School and Bristol Veterinary School) and Dr Katy Turner (Bristol Veterinary School) will carry out data and genomic analysis to model resistance rates of bacteria over time across an individual and, or population. This model will help the team to develop a prediction tool - the ‘Clinical Decision Support System for antimicrobial prescribing’, which will help guide clinicians with their decision-making when prescribing drugs. Targeted antimicrobial prescribing, based on a patient's clinical characteristics and history will reduce exposure to ineffective antimicrobials, and should ultimately improve patient outcomes and reduce AMR.

Professor Dowsey's and Dr Turner's project forms part of a larger study led by Professor Jonathan Sterne's HDR UK Southwest Better Care Hub (based in the Bristol Medical School) to better integrate healthcare data between institutions across the whole of the Southwest region.

Next steps

Workshops are underway to meet with clinicians to discuss and answer priority clinical research questions.