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Last modified: 22 May 2019 17:07

Course Overview

This course is taken by students enrolled on Health Economics for Health Professionals (MSc/PGDip/PGCert). It is concerned with practical issues in the design and conduct of economic evaluation. It covers the principles of the two most common approaches to economic evaluation using individual patient data collected alongside randomised controlled trials, and using decision models to synthesis data from a number of secondary sources. The course highlights the strengths and limitations of each approach, and emphasises their complimentary nature for informing value based health care decision making.

Course Details

Study Type Postgraduate Level 5
Session Second Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus Old Aberdeen Sustained Study No
  • Dr Graham Scotland

What courses & programmes must have been taken before this course?

  • Pg Certificate in Health Economics (Studied)
  • Any Postgraduate Programme (Studied)

What other courses must be taken with this course?


What courses cannot be taken with this course?


Are there a limited number of places available?


Course Description

The aims of the course are to:

1) consider how to identify and extract appropriate data for use in an economic evaluation; and

2) introduce the approaches to economic evaluation based on the analysis of individual patient data from randomised controlled trials, and decision modelling using data from systematic reviews; and

3) understand how these approaches can be used to provide estimates of efficiency inform value based health care decision making.

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers

Details, including assessments, may be subject to change until 31 August 2023 for 1st half-session courses and 22 December 2023 for 2nd half-session courses.

Summative Assessments

Essay (70%)

Continuous assessment (30%)

Formative Assessment

There are no assessments for this course.



Course Learning Outcomes


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