Introduction

Major depressive disorders (MDD) impose a heavy toll on the US economy. Greenberg et al. (1993) estimate the economic burden of depression in 1990 at $44 billion due to the direct health care costs to treat depression ($12.4 billion), mortality cost due to suicide ($7.5 billion), and morbidity costs due to increased absenteeism and reduced productivity at work ($23.8 billion). Specific data on the components of aggregate costs are also available in the literature: reduced work place productivity and disability (Mintz, et al., 1992; Conti & Burton, 1994; Von Korff, et al., 1992; Broadhead, et al., 1990); increased mortality due to suicides (Barraclough, et al., 1974: Brent et al., 1988); and direct medical care costs (Wells et al., 1989; Katon & Sullivan, 1990).

Aggregate cost-of-illness data are an important first step in guiding society in determining how best to allocate scarce health-care resources between competing needs. Depression is an disorder which requires the attention of the US health-care system based on the data quoted above. However, much more detailed data are required to justify the allocation of additional resources to the treatment of depression. Specifically, data are needed on the frequency of, and cost associated with, suboptimal treatment outcomes. This is the focus of this chapter. Other chapters in this text present data on the effectiveness of alternative strategies for the re-treatment of patients who fail to respond to their initial course of therapy. If non-response to available therapies is found to be common and costly, then the deployment of alternative strategies for treating treatment-resistant depression may be economically justified.