title: Optimal test strategy in the case of two tests and one disease.
abstract: Decision-making, especially about test performance, is very complex in nature. Clinical decision analysis can provide tools for doctors which can be used in improving the ordering of laboratory tests. This article describes an approach which is relevant for medical practice and easy to understand, with the goal of obtaining better decisions rather than optimal solutions. The methodology enables a clear understanding of the possibilities and restrictions of test use and needs very little calculation. The cornerstone of the methodology is a graphical representation, by which the benefits of test use are evaluated. Furthermore, a simple algorithm has been developed that can be used to find the optimal solution in the case of two tests. In each step decision rules can be used. In a graphical representation the effect of combining tests can be easily evaluated. If a test combination is chosen one has to decide which sequence is optimal. Finally one has to choose between parallel and series testing. The gain in time of the parallel procedure (and possible gain in effectiveness of treatment) should be compared with the efficiency gain of series testing. The authors conclude that the developed methodology is closer to the intuitive decision-making process than the traditional decision-making techniques and therefore can be used in order to improve the rather intuitive decisions of doctors.
authors.affiliation: Department of Health Economics, University of Limburg, Maastricht, The Netherlands.
authors.forename: A
authors.initials: A
authors.lastname: Ament
authors.forename: A
authors.initials: A
authors.lastname: Hasman
mesh_terms: D019411:Clinical Laboratory Techniques / Q000191:economics / Q000706:statistics & numerical data*; D003362:Cost-Benefit Analysis; D003365:Costs and Cost Analysis; D003657:Decision Making; D003661:Decision Support Techniques; D006801:Humans; D016013:Likelihood Functions; D011336:Probability; D012680:Sensitivity and Specificity; D026712:Value of Life