Decision Modelling for Health Economic Evaluation - ECO00088M
Module summary
This module provides a foundation for understanding and developing decision analytic models used in the evaluation of health care programmes and health technologies.
Related modules
Prerequisite: Evaluation of Health Care
Module will run
| Occurrence | Teaching period |
|---|---|
| A | Semester 2 2023-24 |
Module aims
The aim of this module is to provide an understanding and experience of the application of basic methods of clinical decision analysis to a range of decision problems in health care. In particular it provides:
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a thorough understanding of the way clinical decision analysis can be used to evaluate diagnostic information;
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a framework for the economic evaluation of alternative strategies of patient management;
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and also informs allocative decisions about which health care technologies should be adopted and what research may be required to inform these decisions in the future.
Module learning outcomes
On completing the module the student will be able to: -
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Structure a range of clinical decision problems as decision analytic models.
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Construct and solve these models in a spreadsheet, conduct sensitivity analysis
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Interpret and communicate the results of their analysis.
Identify the limitations of the models they construct and recognise circumstances when more sophisticated methods of decision analysis may be appropriate.
Module content
Week 1: Context and model conceptualisation
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Interpreting a decision problem
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Strategies, outcomes and states
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Types of node within a decision tree
Practical - Structuring the test treatment decision problem in a simple example based on an imperfect diagnostic technology
Week 2: Decision trees
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Developing the test treatment decision:
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Mortality risk associated with test
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Alternative treatment available
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Optimal test cut-off
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Calculating expected utilities of strategies
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Alternative model structures
Practical - Implementing the test treatment decision model in a spreadsheet software
Week 3: Markov models
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Limitations of decision trees
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Transition probabilities and Markov trace
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Tunnel states
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Half-cycle correction
Practical - Using a Markov model to generate utilities in the test treatment decision problem
Week 4: Parameterisation and sensitivity analysis
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Model structure
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Sources of evidence
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Deterministic (scenario) sensitivity analysis
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Probabilistic sensitivity analysis
Practical - Conducting sensitivity analysis and interpreting results from the test treatment decision model
At the end of week 4, students will be assigned to a case study decision problem. From this point on, students will work in their groups in their own time on structuring, parameterising, executing and interpreting a decision model based on the case study. To ensure that students are on the right track there are two seminars timetabled.
Week 6/7: Case study review (model structure) student presentations
At the end of week 6 or beginning of week 7 students are required to give a presentation, as a group, to the rest of the class describing their decision problem, how they intend to structure their decision model and setting out the calculations required to parameterise that model given the evidence with which they are provided.
Week 10: Case study results student presentations
The group-work culminates in a group presentation in week 10 where students, as a group, present their decision model and findings from the case study.
Week 11: Advanced issues in decision modelling in health economics
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Survival analysis
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Patient level simulation and discrete event models
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Dynamic models for infectious diseases
Practical - Using an output from a survival analysis model as an input into a decision model
Week 13: Submission deadline for individual case study report.
Indicative assessment
| Task | % of module mark |
|---|---|
| Essay/coursework | 100 |
Special assessment rules
None
Indicative reassessment
| Task | % of module mark |
|---|---|
| Essay/coursework | 100 |
Module feedback
Following departmental policy, written cohort feedback will be provided online.
Indicative reading
Torrance GW, ed. Chapter 9. In: Methods for the Economic Evaluation of Health Care Programmes / Michael F. Drummond, Mark J. Sculpher, Karl Claxton, Greg Stoddart, George W. Torrance. 4th ed. Oxford University Press,; 2015:xiii, 445 p.:
Briggs A. Decision Modelling for Health Economic Evaluation /. (Claxton K, Sculpher MJ, eds.). Oxford University Press; 2006.
Briggs A. An Introduction to Markov Modelling for Economic Evaluation. PharmacoEconomics. 1998;13(4):397-409.