Health Economic Model for Novel in Vitro Diagnostic Kit for Infective Endocarditis.

The presented economic model estimated costs and benefits of a novel in vitro diagnostic kit for infective endocarditis (IE), developed by Hutman Diagnostics AG (Basel, Switzerland). This new product applies molecular diagnostics to detect bacteria in cardiac tissue faster (see Fig. 1). The focus of the model is set on the diagnostic procedures of Endocardi-Gene ® Tissue (Fig. 1) and of the gold standard procedure as benchmark i.e. is microbial culturing (MC), with respect to cost relevant parameters. Based on these parameters the model describes the expected areas of cost-saving potentials for the diagnostic and therapeutic procedure with respect to the aetiopathology of IE and estimates expected savings for an individual patient in a standard hospital and scales these numbers up for Switzerland (CH), Germany (GER) and the United Kingdom (UK). In a bottom-up approach initial results are derived for one patient and three development scenarios potentially occurring during aetiopathology of IE in a standard hospital. Hereby country-specific cost structures were taken into considerations. Based on these results and annual statistical data for the expected number of treated patients estimates for the annual costs and potential savings for all three countries are derived. Fig.1: Steps of the novel in vitro diagnostic kit for infective endocarditis by Hutman Diagnostics AG. Bibliography Decision tree for aetiopathology of IE As the novel kit provides results within 4-6 hours after sampling instead of 2-3 days by MCs, the following three main outcome scenarios (S) for aetiopathology of IE were investigated by establishing a decision tree: S1-Adjusted hospitalisation and treatment: Decreased average hospi-talisation and earlier specific antibiotic treatment due to quicker diagnosis. S2-Reoperation: Reduction of reoperation frequency. S3-Influence on mortality of recurrent and uncontrolled IE: Reduction of mortality due to fistula formation. Statistics for decision tree The quantitative model uses statistical data for the decision tree from literature and interviews with clinical experts. • Incidence of IE cases of 3.1/100'000 population and year 10 • Implication of required surgery in about 50% of all IE patients 1-3, 5, 9, 11 • Pathogen identification before surgery in about 80% of all cardio-surgery patients 6 • average operative mortality of 10% 4 In conclusion, for CH these assumptions lead for S1 to 67.1 patients on average per year with definitive IE but without diagnosis for a specific pathogen after cardiosurgery by assuming Respective figures for GER and the UK and cases in S2 and S3 are depicted …