Investigating the impact of point of care testing for infections within primary care
Prof A Hay
Dr H Christensen
Applications accepted all year round
Self-Funded PhD Students Only
There is growing interest in the role of point of care tests (POCT) for managing infectious diseases in UK healthcare . Potential impacts include the early identification of the causative microbe (e.g. viral vs. bacterial) for cough/chest infections (CCI) or severity markers for infectious disease. Either could substantially improve the use of antibiotics in primary care (PC) and secondary care, reducing over-treatment and decreasing the selective pressures on antimicrobial resistance – a problem currently at the top of the UK and international public health agendas. While there is some evidence of benefit from Europe and the US, there is a paucity of UK research of the impact, cost-effectiveness and possible negative consequences (for example medicalisation of illness – where patients want the test for otherwise minor, self-limiting illnesses) of POCT.
Aims & Objectives
Aim: Develop and apply mathematical models to predict the potential impact of POCT testing for the management of CCI in PC
- Review and analyse evidence on the use, effectiveness and social impact of POCT in PC in the UK and comparable countries
- Develop and apply a mathematical model of POCT in PC for infections related to CCI to predict the epidemiological impact of POCT
- To gather evidence on the costs relating to POCT and estimate the cost-effectiveness of introducing POCT for CCI in PC
Several POCT are already available to clinicians in PC which could aid the management of CCI, and others are under development. A literature review will be undertaken to ascertain the current use and impact of these tests. Results from trials of new POCT will also be reviewed and analysed, as will data (published literature and routine surveillance) on the epidemiology of the conditions relevant to the POCT. Taking a POCT forward, mathematical models of the management of the disease condition will be developed, and will be applied to predict the potential impact of varying degrees of POCT in PC in the UK. Data on the costs of POCT and disease management will be identified and integrated into the model to undertake a cost-effectiveness evaluation ofPOCTs. Sensitivity analyses will evaluate the robustness of the model findings.
This project is suitable for students with strong mathematical skills at degree level, or equivalent.
1. Howick J et al. BMJ Open 2014;4(8)
2. Little P et al. BMJ 1997;315(7104):350-52