PROJECT SUMMARY FOR THE PUBLIC

Antibiotics are used for the treatment of bacterial infections. Over time, bacteria can become resistant to the effects of an antibiotic. This phenomenon is described as antibiotic resistance. Inappropriate use of antibiotics for non-bacterial infections and prolonged use of antibiotic therapy contribute to the development of antibiotic resistance. As such, antibiotic resistance has become a worldwide public health concern. Stricter control of antibiotic use is required to address this burden. This includes correctly identifying a bacterial infection, using the right antibiotic for the right bacteria and continuing antibiotics for the shortest duration of time. However, the diagnosis of a bacterial infection in an unwell patient and knowing when to stop antibiotics can be challenging. As clinicians, we use a combination of patient signs, blood results and imaging to guide us with these decisions. The conventional tests used can take 2 – 3 days to produce results, as a result delaying potential changes in antibiotic management. Within the last decade, there has been the development of Point-of-care-tests (POCTs). POCTs can provide rapid test results from patient samples analysed outside of the laboratory. An example of POCT includes the recent COVID-19 test. Due to the rapid nature of POCTs, they can result in quick clinical decisions which may include stopping antibiotics when appropriate.

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Previous studies looking into the value of POCTs in decision making were able to show a shorter period of antibiotic use when POCTs were incorporated into clinical guidance. However, not all studies produce this desired outcome. This has partly been accustomed to the prescribing behaviour of a clinician. Prescribing behaviour in this context describes the motivation or demotivation of a clinician to prescribe or stop antibiotics. It is unclear what these factors are that influence prescribing behaviour, especially in the context of stopping antibiotics. 

We have developed an online study to explore these factors using an online survey. The survey will be composed of artificial clinical cases. Clinicians will be questioned on their confidence in their decision and the influencing factors. Further, individual online interviews will examine these factors in-depth.