A MULTIPLE CRITERIA DECISION ANALYSIS FRAMEWORK FOR VALUE BASED ASSESSMENT OF NEW MEDICAL TECHNOLOGIES

Author(s)

Angelis A*, Kanavos P London School of Economics and Political Science, London, United Kingdom

The use of cost/QALY has been criticised for a variety of reasons, including the fact that the QALY does not capture adequately elements associated with burden of disease, aspects of product’s innovation level, and wider socioeconomic implications. No such ‘holistic’ value based assessment (VBA) method has been successfully created yet. Using Multiple Criteria Decision Analysis (MCDA) we develop a new methodological framework for assessing the value of new medical technologies according to the following procedure: Establish the decision context; the decision perspective could potentially adopt a health system’s societal point of view. Identify the options; choose the candidate technologies to be assessed, e.g. antineoplastic drugs for metastatic colorectal cancer. Identify the value objectives/criteria; these should include several technology – disease characteristics and could be divided in the areas of: a) burden of illness; b) therapeutic improvement; c) quality of life benefits; d) innovation level; and e) socioeconomic impact. ‘Scoring’; assess the value associated with the consequences of each criterion for each option, e.g. by adopting a direct rating approach where the judgment of experts is used to rank the magnitude of value. ‘Weighting’; assign weights for each of the criteria to reflect their relative importance to the decision, e.g. by using a swing weighting method implemented in combination with a nominal-group technique where experts agree on the relative contribution of each criterion. Produce a value index; combine weights and scores for each option to derive an overall index of value, e.g. through a weighted average linear additive model. Examine the results and conduct a sensitivity analysis; test the impact of changes in scores and weights on the overall value. The result would subsequently provide evidence on the value of each technology. The methodology could then be applied more practically by linking value index scores with reimbursement and/or pricing decisions.

Conference/Value in Health Info

2013-05, ISPOR 2013, New Orleans, LA, USA

Value in Health, Vol. 16, No. 3 (May 2013)

Code

PRM226

Topic

Methodological & Statistical Research

Topic Subcategory

Confounding, Selection Bias Correction, Causal Inference

Disease

Multiple Diseases

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