Figure 3.

One‐way sensitivity analysis: change to base case incremental savings of $498 (A), change in incremental savings ($) per unit increase of variable (B), and change in incremental savings ($) per $100 increase of variable (C).

1. Results are presented as a shift in the average annual cost savings per individual [Total Cost Savings/(1000 individuals suspected of SLE*4 years)] as a variable is increased/decreased to its upper/lower limit. Abbreviations: Ann, annual; Inc, incremental.
2. The change to incremental savings per unit increase of variable was assessed via a one‐way sensitivity analysis. For example, the range in cost savings differences for MAP specificity was (131.32 + |−131.87|) = 263.19 (see Figure 3A). The range of specificity was (95 – 77) = 18 (Figure 3A). For each unit increase in specificity, cost savings increased by (263.19/18) = 14.62 (Figure 3B). The budget impact model is most sensitive to the specificity of the MAP test, with savings of $14.62 per 1% absolute increase in specificity.
3. The change to incremental savings per $100 increase in cost was assessed in a one‐way sensitivity analysis. The budget impact model is most sensitive to the cost of the MAP test, with a reduction of cost savings of $20 per $100 increase in cost of the test. This figure can be used to evaluate any number of changes to cost assumptions. For example, if one alternately assumes that the prediagnosis cost with SLE is $23 593 ($1000 less than the base case value of $24 593) and assumes that the prediagnosis cost for non‐SLE is $11 796 ($5699 less than the base case value of $17 495), then the change to prediagnosis costs with SLE would change the average annual savings to −$1000 × $0.70/$100 increase = −$7.00, and the change to prediagnosis costs for non‐SLE would change the average annual savings to −$5699 × $4.06/$100 increase = −$231.38. Thus, the average annual cost savings of $498 would adjust from $498 − $238 = $260.