Please note: there may be some adjustments to the teaching arrangements published in the course catalogue for 2020-21. Given current circumstances related to the Covid-19 pandemic it is anticipated that some usual arrangements for teaching on campus will be modified to ensure the safety and wellbeing of students and staff on campus; further adjustments may also be necessary, or beneficial, during the course of the academic year as national requirements relating to management of the pandemic are revised.

Evidence Synthesis MED5524

  • Academic Session: 2022-23
  • School: School of Health and Wellbeing
  • Credits: 10
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Summer
  • Available to Visiting Students: Yes
  • Available to Erasmus Students: Yes

Short Description

This course will teach the methods of systematic review and meta-analysis that are key inputs in health technology assessment and integral to evidence based medicine.


This course will be delivered as a 3 full-day face-to-face course in Glasgow, comprising 11 subject areas.

Requirements of Entry


Excluded Courses





Written Assignment/Coursework - Students will be given and a series of research questions, papers to undertake critical appraisal, and data sets with summary statistics taken from the papers. They will need to answer the research questions by applying methods from the course and writing up as a report (1500 words).

Main Assessment In: August

Course Aims

This course aims to equip students with the necessary skills so they can design and conduct high quality systematic reviews and meta-analyses.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ Critically assess the role of evidence synthesis (including systematic review, meta-analysis of direct, indirect and mixed treatment evidence and realist synthesis) in evidence and technology assessments

■ Create research questions within the systematic review framework and be able to set appropriate eligibility criteria

■ Critically analyse primary studies according to their risk of bias and present results appropriately

■ Create, interpret and critically discuss output after undertaking meta-analyses of different types of data (dichotomous and continuous) and using different approaches (frequentist and Bayesian; fixed and random effects models)

■ Critically assess bias and heterogeneity assessments (cumulative meta-analysis, sub-group analysis and meta-regression)

■ Critically appraise the important aspects of network meta-analysis (making in-direct comparisons)

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.