The evaluation of disease prevention and treatment using simulation models

Health policy models provide measures of the effectiveness and costs of complex health care interventions making it possible to compare different policies. We look at the validity of models of screening, prevention and treatment, focusing on two simulation studies. In designing models, account must be taken of disease trends and changing treatment patterns. The choice of modelling technique and of system boundaries are shown to have an impact on results. Decisions have to be made about data which may be scarce or inappropriate for modelling purposes. Cost-effectiveness measures are based on the ratio of costs to benefits, such as life years saved or quality adjusted life years. These are sensitive to the time period and the discount rates chosen. Policy makers should be aware of these different sources of variability or error. For decision making purposes, the calculation of output measures must be based on the same assumptions.