University of Central Lancashire PhD Studentship in the School of Health Sciences
Applications are invited for two full time PhD (via MPhil) studentships. The studentships are tenable for up to 3 years full-time [subject to satisfactory progress] and will cover the cost of tuition fees at UK/EU rates plus an annual maintenance stipend of £14,057 per year(2015/16 rates). It is expected the successful applicants will commence 1 October 2016. International applicants may apply but will be required to pay the difference in tuition fees.
The School of Health Sciences is offering two full-time PhD (via MPhil) studentships to study one of the following topics:
Evaluating health technologies to support policy development
Health technology assessment plays a vital role in the development of health policy and guidance on the use of drugs, devices, procedures, screening programmes, health promotion and public health policies nationally and internationally. In England and Wales the National Institute for Health and Care Excellence (NICE) rely upon the provision of robust and timely evaluations of the clinical and cost effectiveness of different health technologies to underpin their guidance to the NHS. Evidence synthesis in the form of systematic reviews, meta-analyses and economic evaluations through decision analytic models provide the basis for the assessment of the effectiveness of the different technologies. Limitations in the evidence-base used for evaluating health technologies are well recognised. The effects are reflected in uncertainties in the evaluations undertaken and the guidance provided. The methods used for evaluating health technologies have continued to develop to address these limitations.
In encompassing a different evidence base, new challenges arise in the assessment of the evidence, interpretation of its findings and the development of the ensuing guidance. This PhD will provide the opportunity to examine the different sources of evidence, the evolving methods for their evaluation, the effects on the outcomes of the assessment of health technologies and the potential effects on the guidance developed. It will involve the use of systematic review methods, meta-analysis (including network meta-analysis) and decision-analytic modelling, applying the methods to different case studies to understand the possible consequences for decision makers and policy development.
Statistical methods in the evaluation of the effectiveness of interventions
A. Cluster-randomised controlled trials are often used to avoid the contamination risk inherent when using individual randomisation in many healthcare intervention trials. However, cluster-randomised trials introduce other problems, particularly selection bias and an increase in sample size (due to clustering effects). It has been proposed that individual randomisation may still be preferable if the degree of contamination is limited (Torgerson, 2001) or that more complex designs (e.g. pseudo-cluster randomisation – Borm et al., 2005) should be used. If the contamination can be measured, then causal inferential methods, such as instrumental variables, can be used to adjust effectiveness estimates for contamination. However, the evidence regarding the optimal design and the implications for evidence in relation to the evaluation of effectiveness and cost-effectiveness of healthcare interventions remains limited. This research project will consider the optimal design and analysis options for feasibility and effectiveness trials of complex healthcare interventions.
B. Large general practice and linked hospital datasets are increasingly being used to evaluate the effectiveness of interventions in clinical practice. However, the limitations of these datasets are that they were not collected for research purposes and careful consideration needs to be taken when estimates of effectiveness and cost-effectiveness are required for technology assessments. Methods, such as propensity score matching, exist for balancing intervention groups. However, the extent to which these methods are optimal for such assessments are unknown, particularly given the potential for unrecorded, incomplete or unreliable assessment of variables affecting allocation. This research project will investigate the potential for using a large general practice database (e.g. THIN) and linked hospital data (from HES) to assess the effect of anticoagulant medication on the risk of stroke.
Proposals (500 words) for research in any one of these areas will be considered.
A 2:1 undergraduate degree (or equivalent) in a relevant health, social care, or pertinent methodological subject is essential.
International applicants require an English Language level of IELTs 7.0 (no sub-score below 6.5) or equivalent qualification.
For informal discussion about the [1} Evaluating health technologies to support policy development please contact Professor Andy Clegg email: firstname.lastname@example.org
For informal discussion about  Statistical methods in the evaluation of effectiveness of interventions please contact: Dr Chris Sutton email: email@example.com
For the application form and full details go to:
Completed application forms should be returned to the Research Student Registry email firstname.lastname@example.org
Specification and Application Form
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