OBJECTIVES: Comorbid major depression occurs in approximately ten percent of people suffering from a chronic medical condition such as cancer.  A ‘collaborative care’ approach can be used to systematically identify and treat comorbid major depression.  However, we lack information on cost-effectiveness of overall approach as economic evaluations published to date have focused solely on the treatment stage.  We therefore aimed to use the best available evidence to estimate the cost-effectiveness of the whole approach (both systematic identification and systematic treatment) compared with usual practice, for patients attending specialist cancer clinics. METHODS: A cost-effectiveness analysis using a decision analytic model structured to reflect both the identification and treatment processes.  Evidence was taken from reviews of relevant clinical trials and from observational studies, together with data from a large depression screening service. Sensitivity and scenario analyses were undertaken to determine the effects of variations in depression incidence rates, time horizons, patient characteristics and alternative estimates of treatment effect. Probabilistic sensitivity analysis was also undertaken. RESULTS: Systematic depression management generated more costs than usual practice, but also more quality adjusted life years (QALYs). The incremental cost-effectiveness ratio was £11,765 per QALY and the probabilities of systematic depression management being cost-effective at thresholds of £20,000 and £30,000 per QALY were 0.998 and 1 respectively. Findings were robust to tests of variation in key model parameters. CONCLUSIONS: A combined approach to the systematic identification and treatment of comorbid major depression in cancer patients is likely to be cost-effective at widely accepted threshold values. Systematic depression management may be a better way of generating QALYs for cancer patients than some existing medical and surgical treatments. It could potentially be applied to other chronic medical conditions.