To give (potential) clients a preliminary insight in the cost-effectiveness of their diagnostic test, we developed an online generic decision model. This model allows users to compare the cost and effects of a diagnostic test versus not testing by using data they collected themselves, for example data they collected during clinical studies or in expert interviews. The structure of this generic model is a decision tree, which is a relatively simple method to display steps in the model and their associated outcomes. Using the model can give users a good indication about the current cost-effectiveness of their product, and gives them a starting point in determining subsequent steps for their product development.
You can check our modeling tool now.