New NIHR i4i project to improve antimicrobial prescribing gets underway

members of the project team

A collaboration between medics and engineers will develop intelligent decision support to help doctors prescribe the most appropriate antimicrobials

Antimicrobial resistance has been recognised as a serious, growing global threat and one of the drivers for resistance is the inappropriate use of antibitoics. 

Healthcare professionals who diagnose and treat infections must often do so rapidly to prevent harm to their patients.  Their prescribing decisions can be assisted by providing them with access to treatment recommendations, based on the most likely organism causing the infection (antimicrobial guidelines) and data on local antimicrobial resistance patterns.  

These decision support systems are mostly rule-based, providing easy-to-access policies or guidelines. A new project started by the Faculty of Engineering and Medicine kickstart scheme, and now funded by the NIHR Invention for Innovation scheme has taken this further, developing an intelligent decision support system. This system is capable of considering a greater number of variables and a more complicated number of scenarios than other systems and by using a machine learning algorithm (artificial intelligence or AI) the system is able to continually learn from its previous experiences.

The project team aim for tThe resulting tool to have:

1. The ability to display data from NHS servers on mobile and tablet devices at the patient bedside

2. A unique machine learning algorithm, developed in-house to provide advanced, intelligent decision support for clinicians for optimised antimicrobial choices

3. A population pharmacometric model to provide individualised antimicrobial dosing for individual patients

4. A patient engagement tool to facilitate shared decision making across a range of complex healthcare pathways