Sensitivity Analysis

Sensitivity analysis is a method used to determine the level of confidence associated with the conclusions of an economic evaluation. It involves systematically varying key assumptions and input parameters of the evaluation to observe the impact on the results. This process helps  identify which variables have the most influence on the outcome and assesses the robustness of the conclusions.

Key aspects of sensitivity analysis include:

– Purpose: To illustrate the degree of uncertainty and assess the robustness of the conclusions drawn from an economic evaluation. It provides decision-makers with insights into how sensitive the results are to changes in key assumptions and parameters.

– Types of Sensitivity Analysis:

– One-Way Sensitivity Analysis: Involves varying one input parameter at a time to see its impact on the outcome.

– Multi-Way Sensitivity Analysis: Involves varying multiple input parameters simultaneously to assess their combined effect on the outcome.

– Threshold Analysis: Determines the tipping point at which a change in an input parameter would alter the decision based on the evaluation’s output.

– Probabilistic Sensitivity Analysis (PSA): Uses stochastic methods to produce a distribution of outcomes based on the distributions of input parameters. This method provides a more comprehensive picture of uncertainty by considering the variability of multiple parameters simultaneously.

– Implementation in Model-Based Evaluations: Sensitivity analysis in model-based economic evaluations involves varying:

– Key Input Parameters: Such as costs, utilities, probabilities, and other variables that influence the model’s outcome.

– Structural Assumptions: How the input parameters are combined within the model, which can include the choice of model structure, time horizons, and discount rates.

– Importance in Decision-Making: Sensitivity analysis provides valuable information about the robustness of the economic evaluation’s findings. It helps decision-makers understand the range of possible outcomes and the likelihood of different scenarios, thereby aiding in making informed choices. Additionally, it highlights areas where further data collection might be beneficial to reduce uncertainty.

Sensitivity analysis is a critical component of the economic evaluation process, ensuring that the results are robust and reliable, and that decision-makers are fully aware of the potential variability and uncertainty inherent in the evaluation.

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