Instituto Nacional de Traumato-Ortopedia (INTO) administrates the Enoxaparin drug to prevent deep vein thrombosis (DVT) after extensive orthopedic surgeries. Nevertheless, new oral anticoagulants that offer more comfort and efficacy, but present higher risk of bleeding, have been putting in question the use of Enoxaparin. Making use of the MACBETH method, this study develops a Multicriteria Value Measurement model to evaluate such drugs.

MACBETH was applied in helping INTO to evaluate two drugs (Rivaroxaban and Enoxaparin), taking into account drug benefits and risks, through a series of interviews and decision conferences attended by INTO stakeholders that acted as evaluators in the model-building process, supported by M-MACBETH DSS (www.m-macbeth.com). Following MACBETH preference elicitation process, the evaluators were asked to make qualitative pairwise comparison judgements of difference in value between stimuli for constructing quantitative value and weighting scales. These scales allow measuring the relative value of the drugs on each evaluation criterion, separately and globally. The value measurement process was informed by a literature review and meta-analysis of randomized clinical trials with a critical appraisal of the evidence.

We report a model-structure with eight criteria, hereafter presented by decreasing order of their weighting: Death from any cause, Clinically significant bleeding, Proximal DVT, Distal DVT, Existence of antidote, Thrombocytopenia, Costs, and Comfort. From the value model developed and after performing sensitivity and robustness analyses, Rivaroxaban was considered a robust option for thrombosis prophylaxis, under the MACBETH value framework and at the light of a simple additive aggregation of those eight criteria.

This study shows how a value measurement socio-technical framework, combining MACBETH with scientific evidence within a participatory group evaluation process, can support health technology assessment in a user-friendly and effective way. MACBETH facilitates transparent and robust decision-making in the face of complex evaluation problems that the hospital often faces.