BACKGROUND: The economic effects of Point-of-Care (POC) coagulation testing including Multiple Electrode Aggregometry (MEA) with the Multiplate device have not been examined. METHODS: A health economic model with associated clinical endpoints was developed to calculate the effectiveness and estimated costs of coagulation analyses based on standard laboratory testing (SLT) or POC testing offering the possibility to assess platelet dysfunction using aggregometric measures. Cost estimates included pre- and perioperative costs of hemotherapy, intra- and post-operative coagulation testing costs, and hospitalization costs, including the costs of transfusion-related complications. RESULTS: Our model calculation using a simulated true-to-life cohort of 10,000 cardiac surgery patients assigned to each testing alternative demonstrated that there were 950 fewer patients in the POC branch who required any transfusion of red blood cells. The subsequent numbers of massive transfusions and patients with transfusion-related complications were reduced with the POC testing by 284 and 126, respectively. The average expected total cost in the POC branch was 288 Euro lower for every treated patient than that in the SLT branch. CONCLUSIONS: Incorporating aggregometric analyses using MEA into hemotherapy algorithms improved medical outcomes in cardiac surgery patients in the presented health economic model. There was an overall better economic outcome associated with POC testing compared with SLT testing despite the higher costs of testing.
BACKGROUND: The economic effects of Point-of-Care (POC) coagulation testing including Multiple Electrode Aggregometry (MEA) with the Multiplate device have not been examined. METHODS: A health economic model with associated clinical endpoints was developed to calculate the effectiveness and estimated costs of coagulation analyses based on standard laboratory testing (SLT) or POC testing offering the possibility to assess platelet dysfunction using aggregometric measures. Cost estimates included pre- and perioperative costs of hemotherapy, intra- and post-operative coagulation testing costs, and hospitalization costs, including the costs of transfusion-related complications. RESULTS: Our model calculation using a simulated true-to-life cohort of 10,000 cardiac surgery patients assigned to each testing alternative demonstrated that there were 950 fewer patients in the POC branch who required any transfusion of red blood cells. The subsequent numbers of massive transfusions and patients with transfusion-related complications were reduced with the POC testing by 284 and 126, respectively. The average expected total cost in the POC branch was 288 Euro lower for every treated patient than that in the SLT branch. CONCLUSIONS: Incorporating aggregometric analyses using MEA into hemotherapy algorithms improved medical outcomes in cardiac surgery patients in the presented health economic model. There was an overall better economic outcome associated with POC testing compared with SLT testing despite the higher costs of testing.