Background: Translating the results of test accuracy evaluations, and reviews thereof, into recommendations for practice is acknowledged to be challenging. Part of this challenge is that policy decisions are ideally based on clinical effectiveness (impact on patient outcome) and cost-effectiveness, whereas DTARs deliver estimates of the error rates associated with making diagnoses using particular tests. This information although necessary, is unlikely to be considered sufficient by policy-makers. One suggested solution is to encourage reviewers to introduce information about the consequences of true positive, true negative, false positive and false negative results in order to anticipate what patient outcome might be. The GRADE system does this too, but also encourages quantification and suggests consideration of costs. Economic modelling is a more formal approach to the structuring of a decision and provides a framework for collating separate sources of information on different aspects of the wider impact of a new initiative. It does not have to incorporate costs. There is a long history of using it as an evaluative tool for tests because it is uncommon for the effect of tests on patient outcome to be assessed directly. Most commonly we have evidence on accuracy, and independently evidence on the effectiveness of treatments which might be applied when the test result is positive. Objective: To consider the potential role of modelling in assisting knowledge translation of DTARs. Methods: Case-study. Results: A simple model will be prepared, or adapted should an existing model be available, to complement one of the existing Cochrane DTARs Conclusions: Provisionally modelling is likely to be of assistance in knowledge translation and may indeed challenge the appropriateness of current approaches. The difficulty for the Cochrane Collaboration would be how to incorporate the results of modelling exercises into an already complicated and daunting review format.