Strategies for Diagnosing Deep Vein Thrombosis -a Cost Effectiveness Analysis

Economic evaluations are used in the health care sector to help decision makers allocate resources. The objective of this study is to evaluate the cost effectiveness of a new diagnostic algorithm of deep vein thrombosis. Patients with suspected deep vein thrombosis are common at emergency departments, although few actually have the disease. The new diagnostic algorithm combines a pre-test probability score and a D-dimer test, avoiding costly diagnostic imaging. The strategy is compared to “the old algorithm”, which involves diagnostic imaging, and an alternative implementation of the new algorithm. The analysis is made from health care budget perspective, as well as a societal perspective. A cost effectiveness analysis was performed using a decision model. The same effectiveness was assumed for the different strategies. A decision tree was generated, incorporating the different strategies. A data material comprising 357 patients was obtained from a previous study made in seven hospitals in southern Sweden. The total cost of the new algorithm is estimated to €403 per patient, compared to the old and the alternative implementation of the new algorithm which are estimated to €576 and €419 respectively. Thus, the new algorithm is the most cost effective strategy and implies great savings potential not only for the health care sector, but also to society as a whole