Cluster randomised controlled trials are widely used in health service evaluation. A common approach is a parallel design where clusters in control and intervention arms receive their respective intervention throughout the trial period. An alternative is the stepped wedge design where all clusters are first allocated to the control arm followed by exposing to intervention sequentially until all clusters are exposed. The stepped wedge design has been increasingly applied in recent years.
In many countries, decision makers need to judge both the scientific value (clinical effectiveness) and social value (cost effectiveness) of a treatment. Economic evaluations are commonly performed alongside clinical trials to produce evidence of cost-effectiveness. Methodology for economic evaluation conducted alongside parallel cluster randomised trials has developed in recent years. Evidence of cost-effectiveness from stepped wedge trials began to emerge from 2014, but a recent review of 54 protocols and trial reports found only 16 reported methods appropriate to the stepped wedge design (Lung, Si, Hooper & Di Tanna, DOI:10.1007/s40273-020-00963-x). With the rapid growth in stepped wedge trials, there is an urgent need to improve methods and disseminate them in order to increase their adoption.
The project aims to identify appropriate statistical methods for economic evaluation alongside stepped wedge trials. It includes four objectives:
(1) To review and critically assess methodological work.
(2) Building on existing work, to compare methodological approaches e.g. using simulation, and potentially propose and apply novel methods such as hierarchical Bayesian models.
(3) To facilitate their use, for instance by publishing a tutorial and practical guidance.
(4) To develop a checklist for appropriate statistical methods.
The student will work closely with both supervisors at QMUL. Professor Hooper is a world leading expert on the design and analysis of stepped wedge trials. Dr Feng is a health economist with experience in conducting economic evaluation alongside parallel cluster randomised trials. She will contribute to all four objectives of the project, and provide support to the student on a day-to-day basis. Professor Di Tanna is the lead author of the published review of economic evaluation in stepped wedge trials and is conducting ongoing research in this area, and will input to the project as an external advisor.
The studentship will be embedded within the Centre for Evaluation & Methods in the Wolfson Institute of Population Health at QMUL. The Centre hosts two UKCRC-registered Clinical Trials Units, and has an international reputation for its research on stepped wedge trial design, as well as a thriving health economics group with strong methodological interests.
Trials run in collaboration with the two Clinical Trials Units all closely involve patients and the public, and the Wolfson Institute of Population Health has a Public Advisory Panel representing the social, cultural and ethnic diversity of East London. The student will have opportunities to explore how patient and public involvement could add value to their project.
HOW TO APPLY
You are applying for a PhD studentship from the MRC TMRP DTP. A list of potential projects and the application form is available online at:
http://www.methodologyhubs.mrc.ac.uk/about/tmrp-doctoral-training-partnership/
Please complete the form fully. Incomplete forms will not be considered. CVs will not be accepted for this scheme.
Please apply giving details for your first choice project. You can provide details of up to two other TMRP DTP projects you may be interested in at section B of the application form.
Before making an application, applicants should contact the project supervisor to find out more about the project and to discuss their interests in the research before 09 January 2023.
The deadline for applications is 4pm (GMT) 16 January 2023. Late applications will not be considered.
Completed application forms must be returned to: [Email Address Removed]
Informal enquiries may be made to Dr Yan Feng - [Email Address Removed]
Continue with Facebook
