Calibrating Models in Economic Evaluation
2011
This article provides guidance on the theoretical underpinnings of different calibration methods used for mathematical models for economic evaluations. The calibration process is divided into seven steps and different potential methods at each step are discussed, focusing on the particular features of disease models in economic evaluation. The seven steps are (i) Which parameters should be varied in the calibration process? (ii) Which calibration targets should be used? (iii) What measure of goodness of fit should be used? (iv) What parameter search strategy should be used? (v) What determines acceptable goodness-of-fit parameter sets (convergence criteria)? (vi) What determines the termination of the calibration process (stopping rule)? (vii) How should the model calibration results and economic parameters be integrated?
Models based on scientific knowledge of disease use simplifying assumptions, and contain input parameters with varying levels of uncertainty. Calibration is one tool for estimating uncertain parameters and more accurately defining model uncertainty. Calibration involves the comparison of model outputs with empirical data, leading to the identification of model parameter values that achieve a good fit. The lack of standards in calibrating disease models in economic evaluation can undermine the credibility of calibration methods. In order to avoid public skepticism regarding calibration, the authors present a unified approach to the problem and report the various methods used.
Calibrating Models in Economic Evaluation
Source:
Vanni T, Karnon J, Madan J et al. Calibrating Models in Economic Evaluation: A Seven-Step Approach. PharmacoEconomics 2011; 29 (1): 35-49. https://doi.org/10.2165/11584600-000000000-00000