BACKGROUND: Routine outcome monitoring may improve clinical services but remains controversial, partly because the absence of a control group makes interpretation difficult. AIMS: To test a computer algorithm designed to allow practitioners to compare their outcomes with epidemiological data from a population sample against data from a randomised controlled trial, to see if it accurately predicted the trial's outcome. METHOD: We developed an ;added value' score using epidemiological data on the Strengths and Difficulties Questionnaire (SDQ). We tested whether it correctly predicted the effect size for the control and intervention groups in a randomised controlled trial. RESULTS: As compared with the a priori expectation of zero, the Added Value Score applied to the control group predicted an effect size of -0.03 (95% CI -0.30 to 0.24, t = 0.2, P = 0.8). As compared with the trial estimate of 0.37, the Added Value Score applied to the intervention group predicted an effect size of 0.36 (95% CI 0.12 to 0.60, t = 0.1, P = 0.9). CONCLUSIONS: Our findings provide preliminary support for the validity of this approach as one tool in the evaluation of interventions with groups of children who have, or are at high risk of developing, significant psychopathology.