Jeroen van de Pol

98 Chapter 4 with impact, showing a probability of 93.6% that a CMR is cost saving and a 90.1% probability of also giving a reduction in the number of severe complaints (Figure 2C). The acceptability curves are shown in Supplementary Figure 1. probabi of 93.6% that a CMR is cost savi g and a 90.1% probability of also giving a reduction in the number of severe complaints (Figure 2C). The acceptability curves are shown in Supplemen a) b) c) Figure 2a, b, c: Cost-effectiveness plane for the incremental cost-effectiveness ratios (ICERs) determined as a) costs/QALY measured with EQ-5D-5L health utility values, b) costs/QALY measured with EQ-VAS health utility values and c) costs/effects determined as reduced complaints with impact. The x-axis shows the incremental effects and the y-axis shows the incre -600 -500 -400 -300 -200 -100 0 100 200 300 400 -1 -0,5 0 0,5 1 1,5 -600 -500 -400 -300 -200 -100 0 100 200 300 400 -0,02 -0,01 0 0,01 0,02 -600 -500 -400 -300 -200 -100 0 100 200 300 400 -0,02 -0,01 0 0,01 0,02 0,03 Figur 2a, b, c: Cost-effectiven ss plane for the incremental cost-effectivene s ratios (ICERs) determined as a) costs/QALY measured with EQ-5D-5L health utility values, b) costs/QALY measured with EQ-VAS health utility values and c) costs/effects determined as reduced complaints with impact. The x-axis shows the incremental effects and the y-axis shows the incremental costs in euros. Abbreviation: QALY = quality-adjusted life year. Deterministic sensitivity analysis Results from the deterministic sensitivity analysis (DSA) are shown in Figure 3. A DSA determines the impact of uncertainty of individual cost parameters on the cost-saving or cost-introducing aspect of an intervention. Bars on the right-hand side show how uncertainty can increase the costs of an intervention and bars on the left-hand side show how uncertainty decreases the costs. The results show that the costs of the intervention, the costs of secondary care (including hospital