Cost-benefit analysis (CBA) is by no means the right tool to apply to your problem, since in CBA both cost and results (and this latter point is very tricky to perform) are expressed in montery terms. Usually, benefits are expressed in mometary terms via the Willingness-To-Pay approach.
Cost-effectivenes analysis (CEA) might be the right choice, provided that:
-you consider an outcome that is common to all the alternatives under investigation (e.g., number of cases of a given disease that are correctly diagnosed);
-you perform an incremental analysis of cost and effectiveness;
- costs and outcomes (if any) that occur in the future are properly discounted (as Michelle advised you to);
- you check the robustness of your base case findings via a comprehensive set of sensitivity analyses (deterministic; probabilistic; scenario);
- you provide the readers wit soem guidance about the affordability of the incremental cost-effectiveness ratio (ICER) obtained in your CEA. With diagnostic tests this step is usually tricky (what is the amount of money decision-makers are willing to pay for identifying a case of a given disease?), unless your results contribute to populate a wider model that links your CEA results to (say) years of live saved or quality-adjusted life years (for which threshold values for ICER are indeed available.
An authoritative source for these (and many other) topics concerning the economic evaluation of health care programmes is: Drummond, M.F.; Sculpher, M.J.; Torrance, G.W.; O'Brien, B.J.; Stoddart, G.L. Methods for the economic evaluation of health care programme. Third edition. Oxford: Oxford University Press, 2005.