The need for an iterative process for assessing economic outcomes associated with SSRIs.

Pharmacotherapeutic advances in the treatment of depression have included the development of the selective serotonin reuptake inhibitors (SSRIs), thereby providing alternatives to tricyclic antidepressants. Concurrent with these events have been significant structural (e.g. pharmaceutical formularies) and regulatory (e.g. required pharmacoeconomic evaluations) changes in the delivery, financing, and oversight of healthcare programmes throughout the world. International cost-containment initiatives are increasingly mandating a demonstration of value for money, defined in terms of a measurable health and/or financial outcome, and, in the case of medicines, attributable to a given expenditure, for a given pharmacotherapeutic option. We examine the inherent strengths and weaknesses of 5 study designs used to discern and contrast financial outcomes stemming from the use of antidepressant pharmacotherapy for the treatment of depressive illness [randomised controlled trials (RCTs); meta-analyses; decision-analytical models (DAMs); retrospective database investigations; randomised naturalistic inquiry]. We argue that the economic appraisal of pharmacotherapy requires an iterative process extending from the developmental (RCTs; meta-analyses; DAMs) through to the postmarketing phase (database reviews; naturalistic inquiry), thereby resulting in a portfolio of evidence as to the safety, efficacy and effectiveness of a given pharmacotherapeutic category (e.g. SSRIs) and/or a specific medication. Database reviews, while nonrandomised, and prospective naturalistic inquiry afford greater insight into the patterns of use and financial merits of prescribing specific pharmacotherapeutic options for the treatment of depression within the context of clinical practice as compared with RCTs, meta-analyses and DAMs. The portfolio of evidence to date indicates that the first-line use of SSRIs in the treatment of depression is clinically warranted, and represents value for money.