Major depressive disorder (MDD) is one of the most prevalent mental disorders in the US with social costs upwards of $43 billion. The Agency for Health Care Policy and Research has disseminated diagnosis and management guidelines for MDD in primary care. OBJECTIVE: Our aim was to develop a simulation model to evaluate clinical and economic consequences of following AHCPR treatment recommendations. A secondary objective was to create a tool that could be used by health plan decision-makers to assess the value of alternative treatments for MDD. METHODS: A discrete state simulation model was developed to evaluate primary care management of adults with MDD following the AHCPR guidelines. The perspective of the model was that of the health plan; the time horizon was 1 year from the initiation of pharmacotherapy. Uncertainty was evaluated using Monte Carlo simulation techniques. Endpoints included clinical remission, hospitalization for MDD or psychiatric referral for treatment failure. Efficacy and safety data were drawn from published randomized, nonrandomized, and synthesized studies and cost data were derived from modal reimbursement rates from a large managed care organization in Washington State. RESULTS: The results of the base case simulation demonstrated that initial treatment of MDD with serotonin reuptake inhibitors provided better clinical outcomes at similar costs when compared to tricyclic antidepressants. CONCLUSION: Simulation models of treatment guidelines are an important and useful extension of outcomes research because they can simultaneously account for costs and effectiveness not otherwise available from a single published study. Further, models such as this can prove useful to health plan decision-makers interested in the ex ante evaluations of individual antidepressant agents for formulary decisions.