Tackling heterogeneity: The full costs include those of research necessary to support the analyses

摘要

In this issue of Medical Decision Making, Espinoza and others take on an important problem-understanding how heterogeneity can affect estimates of cost-effectiveness-and hence (where employed) how this in turn affects treatment recommendations. They analyze the consequences of assuming homogeneous treatment effects (and hence identical cost-effectiveness measures) in a population that in fact is heterogeneous. Espinoza and others establish a framework for considering how fine to make the granularity in cost-effectiveness analyses (CEA), measuring the incremental benefits from finer and finer granularity and then imposing increasing costs of achieving that granularity in the model. As any good economic model will do, once we have increasing costs and diminishing marginal benefits (both of which are readily present in this situation), we find an optimum solution. In general, the increasing costs in their work arise from costs within a health care system, such as the costs of implementing the intervention in more subgroups.