| Unit name | Quantitative methods for economic evaluation and health policy analysis |
|---|---|
| Unit code | BRMSM0047 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 1B (weeks 7 - 12) |
| Unit director | Professor. Hollingworth |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
Concepts in the economics and policy of health and care |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | Bristol Medical School |
| Faculty | Faculty of Health Sciences |
The aim of this unit is to provide an introduction to the quantitative methods commonly used in economic evaluation and health economic policy analyses. These methods will be introduced within the context of experimental studies (i.e. randomised controlled trials [RCTs]) to compare the cost and outcomes of health care in an economic evaluation and various observational study designs to explore the effect of policy changes on health and health-related costs. Students will build on the introduction to economic evaluation given in the module ‘Concepts in the economics and policy of health and care’ by exploring analytic methods for conducting economic evaluation in practice, including the analysis of cost and outcome data. The application of quantitative methods in economic evaluation will begin with methods for describing the data and move on to the calculation of summary statistics and the estimation and representation of uncertainty using methods including bootstrapping and seemingly unrelated regressions. More advanced methods including imputation of missing data and analysis of clustered data will be introduced. Quantitative methods for observational data will include ordinary least squares regression models; regressions for count data; generalized linear models for cost data; and an introduction to more advanced methods including interrupted time series and instrumental variable analyses to identify potentially causal associations. We will discuss reporting guidelines for economic evaluation and observational studies using routine data.
By the end of the Unit, students should be able to:
The unit will be delivered using blended learning. There will be a three-day teaching block (18 hours). This will comprise a mixture of presentations on methods, examples of quantitative health economic and policy research and interactive practical sessions, allowing students to get hands on experience of data analysis using Stata with direct feedback from tutors and peers. Online asynchronous teaching (25 hours) will be linked with the weekly tutorials (7 hours, weekly across TB1B). Students will have the opportunity to learn about the theory and quantitative methods asynchronously and have this learning reinforced through Q&A sessions; quizzes and individual and group exercises during the weekly tutorials. Tutorials will also allow interaction with peers and tutors and completion of formative assessment tasks. The Unit also requires self-study of around 150 hours.
Formative assessment of the research design and quantitative methods discussed in this unit will be threaded through the unit in the three-day face-to-face teaching block and the weekly tutorials, using class quizzes; individual and group exercises and presentations on study design and analysis plans; and practical work based on de-identified health datasets with feedback from tutors and peers (ILOs 1-4). Within the asynchronous materials students will critique a published quantitative research paper and using a discussion board identify strengths, limitations and policy implications (ILOs 5). There will be a specific formative assessment to generate a brief analysis plan for their summative assessment on which students will receive feedback from the tutor and peers to make sure they are on the right lines before starting work on the planned analysis.
The summative assessment will be a single assignment with marks weighted for specific elements. This will test students on their ability to develop an analysis plan and use appropriate quantitative methods (e.g. regression) to analyse, report and interpret data in light of their understanding of study design (ILOs 1-5). Students will be able to choose from a small number of pre-specified research questions using publicly available health datasets (e.g. open prescribing or hospital episode statistics) and write up their analysis in the form of a Policy Brief (3000 words); 30% of the marks will be given for defining the problem and stating the options, with the remaining 70% of the mark for the quantitative analysis and interpretation and implications. Students will need to obtain a mark of 50% to pass the Unit.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. BRMSM0047).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the Faculty workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an
assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
