To build on Module 3 (Introduction to Economic Health Care Evaluation) and Module 6 (Advanced Topics in Economic Evaluation) in particular. The module describes the purpose of decision analytic modelling and the methods used to undertake decision analytic modelling.
Module learning outcomes
Upon successful completion of the module you should be able to:
Explain and discuss the methodological problems associated with the economic analysis of patient level data carried out alongside randomised clinical trials (RCTs).
Explain the rationale for decision modelling in economic evaluation and describe its terminology.
Be able to structure and analyse decision problems using a decision tree and implementation of a Markov model.
Understand the potential role of other modelling approaches such as individual patient sampling, semi Markov models and dynamic infectious disease models.
Identify model inputs which are subject to second order uncertainty and select appropriate probability distributions to characterise this uncertainty.
Interpret the results of a Monte Carlo simulation including cost-effectiveness acceptability curves.
Understand and implement modelling methods for diagnostic technologies.