M J Nuijten1. 1. Medtap, Jisp, Amsterdam, The Netherlands.
Abstract
OBJECTIVE: The aim of the present study is to describe a refinement of a previously presented method, based on the concept of point sensitivity, to deal with uncertainty in economic studies. DESIGN: The original method was refined by the incorporation of probability distributions which allow a more accurate assessment of the level of uncertainty in the model. In addition, a bootstrap method was used to create a probability distribution for a fixed input variable based on a limited number of data points. The original method was limited in that the sensitivity measurement was based on a uniform distribution of the variables and that the overall sensitivity measure was based on a subjectively chosen range which excludes the impact of values outside the range on the overall sensitivity. PATIENTS AND PARTICIPANTS: The concepts of the refined method were illustrated using a Markov model of depression. MAIN OUTCOME MEASURES AND RESULTS: The application of the refined method substantially changed the ranking of the most sensitive variables compared with the original method. The response rate became the most sensitive variable instead of the 'per diem' for hospitalisation. CONCLUSIONS: The refinement of the original method yields sensitivity outcomes, which greater reflect the real uncertainty in economic studies.
OBJECTIVE: The aim of the present study is to describe a refinement of a previously presented method, based on the concept of point sensitivity, to deal with uncertainty in economic studies. DESIGN: The original method was refined by the incorporation of probability distributions which allow a more accurate assessment of the level of uncertainty in the model. In addition, a bootstrap method was used to create a probability distribution for a fixed input variable based on a limited number of data points. The original method was limited in that the sensitivity measurement was based on a uniform distribution of the variables and that the overall sensitivity measure was based on a subjectively chosen range which excludes the impact of values outside the range on the overall sensitivity. PATIENTS AND PARTICIPANTS: The concepts of the refined method were illustrated using a Markov model of depression. MAIN OUTCOME MEASURES AND RESULTS: The application of the refined method substantially changed the ranking of the most sensitive variables compared with the original method. The response rate became the most sensitive variable instead of the 'per diem' for hospitalisation. CONCLUSIONS: The refinement of the original method yields sensitivity outcomes, which greater reflect the real uncertainty in economic studies.