Mauskopf J, Earnshaw SR. Uncertainty analysis. In: Mauskopf J, Earnshaw SR, editors. Budget-impact analysis of health care interventions: a practical guide. 1st ed. Cham: Switzerland. Springer International Publishing AG; 2017. p.129-38. doi: 10.1007/978-3-319-50482-7.


The purpose of budget-impact analysis is to project the potential future impact of the introduction of a new drug or other intervention on payer or provider budgets. Because estimates of current input values as well as assumptions about the structural model elements and changes in many input values over the analysis time horizon are needed, the results are estimated with uncertainty. Therefore, it is important for the model to include a method for performing uncertainty analyses. Uncertainty analyses allow the user to test the impact of different structural elements, assumptions, and input parameter values on the outcomes of the budget-impact analysis. In this chapter, methods for testing the impact on the results are presented (1) for alternative scenarios created using data and assumptions known to the budget holder and (2) for estimated ranges of input parameter values using uncertain data estimates and assumptions.

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