Current budgetary restrictions in health systems have increased the influence of economic evaluation studies on decision making. Nevertheless, uncertainty about the parameters used in pharmacoeconomic models is inevitable and may affect the conclusions drawn. The present article aims to review the main methods proposed to quantify the uncertainty inherent in pharmacoeconomic evaluations applied to health technologies. The most accurate pharmacoeconomic estimations are obtained by probabilistic methods of uncertainty analysis such as Monte Carlo simulation, repetitive sampling and the Fieller method. Alternatives to these methods are calculation of the cost-effectiveness acceptability curve or net health benefit. Equally, the economic impact of uncertainty in the pharmacoeconomic models used in the decision-making process can be estimated by obtaining what is known as the value of perfect information.
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