Thursday 15 February 2018, 12.15PM to 1.15pm
Speaker(s): Matthew Taylor, York Health Economics Consortium, University of York
OBJECTIVES: In probabilistic sensitivity analysis (PSA), it is typical to see distributions assigned to all (relevant) parameters in a model. However, attention is only usually paid to estimating covariance or interactions between a small number of parameters, if any at all. This study explores the impact of interaction and non-interaction assumptions on the outcomes of PSA.
METHODS: A simple eight-state Markov model was developed, with corresponding input parameters for transition probabilities, costs and utilities for all health states. A range of alternative approaches to parameter correlation were taken, ranging from zero correlation to extreme cases such as ‘full dependent interaction’. These were applied to a range of different structural assumptions in the model (for example, rather than a single input parameter for 'monthly cost of health state X', individual parameters were created for 'cost of physician visits', 'cost of tests', 'cost of drugs', 'cost of hospital visits', etc). The impact of all permutations on the shapes of the PSA scatter plot and CEAC was recorded.
RESULTS: The analysis demonstrates that, if a specific input parameter is broken down into several components which are varied independently, then it is likely that the variation in each parameter will cancel out the effect of the changes in the other parameters, suggesting a false level of certainty in the PSA's results. The extent of this outcome depended on a number of factors, such as the complexity of the model structure, the proximity of the model’s base case results to the cost-effectiveness threshold and the level of artificial correlation applied to each parameter.
CONCLUSIONS: This analysis demonstrates the outcomes of a PSA can be influenced by the level of detail that the modellers choose to include and, counterintuitively, modellers can create 'false' confidence in PSA results by including more parameters. A number of recommendations are provided for the critical appraisal of probabilistic model outputs.
Location: Alcuin A Block A019/20
Who to contact
For more information on these seminars, contact:Thomas Patton
Economic evaluation seminar dates
- Thursday 17 January
Edward Cox, CHE, University of York
- Thursday 21 February
Sebastian Hinde, CHE, University of York
- Thursday 21 March
Alessandro Grosso, CHE, University of York