Exploring and maximising the impact of meta-analyses

Description

About the Project 

When several treatment options exist for a condition, network meta-analysis (NMA) can be used to combine results from multiple trials to estimate the relative effectiveness of the treatments and potentially ranking them in order of effectiveness.  Conventional pair-wise meta-analysis can also be used but is limited to comparing only two treatments simultaneously so requires multiple analyses. 

Systematic reviews of trials are considered the highest level of evidence and are often used to inform new treatment policies, such as World Health Organisation or NICE (NHS) guidelines, which are followed by healthcare workers in practice.  

To reduce research waste and improve efficiency, it is important to maximise the uptake of meta-analyses in clinical practice guidelines and ensure such guidelines are being followed in practice. Potential beneficiaries of meta-analyses could be patients, their families, healthcare workers, policy makers, and review and trial methodologists. However, the impact of meta-analyses on its beneficiaries (e.g. improved health), is under-researched.  

Aims and Objectives 

The aim of this research is to quantify the uptake of meta-analyses in clinical treatment guidelines, to identify other impacts of meta-analyses, and to explore characteristics of meta-analyses that affect impact. 

Methodology 

This is an excellent opportunity for a student to develop strong statistical and qualitative research skills while training with leading experts in evidence synthesis.

We will identify the impact of meta-analyses for different beneficiaries, through a review of published meta-analyses are treatment guidelines, and surveying and interviewing review authors.

We will explore, through statistical analyses, factors that could potentially affect the uptake of a meta-analysis into clinical guidelines (e.g. number of trials, quality of meta-analysis, funding, dissemination strategies, type of meta-analysis -NMA, pairwise) and therefore how impact can be maximised. 

The student will become an expert in the impact of meta-analysis and will develop recommendations for evidence synthesis researchers to consider so that the impact of their work could be improved.

Application information

This project will be based in the Department of Health Data Science at the University of Liverpool. To apply for the position, please email donegan@liv.ac.uk attaching a covering letter, CV and details of 2 referees.