Multicriteria decision analysis MCDA

When trade-offs exist, no single compound will stand out uniquely as the optimum drug for the market, ranked hrst on all measures of performance. Rather, a set of compounds will be considered that, on current knowledge, span the optimal solution to the problem. These compounds are those for which there is no other compound that offers equivalent performance across all criteria and superior performance in at least one. In multicriteria decision analysis (MCDA) terminology, they are known as Pareto-optimal solutions. This concept is illustrated by the two-criteria schematic in Figure 11.3. 

There are two main approaches to informing decisions that take account of economic factors. One is cost benefit assessment (CBA) and the other is multicriteria decision analysis (MCDA). It is not the purpose of this document to provide detailed guidance about these techniques, but we offer some comments in the context of standard setting (Text Box C). For a more detailed appreciation of CBA, refer to... 

Conducting a BRA requires applying evaluative judgments on the benefit and risk outcomes. A pure mathematical method is not appropriate, but the use of a formal decision-making process involving decision analysis is suitable for and has been applied to the BRA. As the BRA needs to account for multiple benefit and risk criteria, multicriteria decision analysis (MCDA), using a decision-tree model, is appropriate and has been adapted for the BRA to allow for systematic decision making in complex situations. 

It is somehow paradox, that the good transparency supported by modular scenarios gives the impression that expectations will offer sufficient evaluation results, superfluous the need to model data. Anyway, discrepancies between expected and modelled evaluation results need to be removed, as stakeholders will hardly accept an evaluation result, which extensively disagrees with their expectations. HDT-originated analysis tools such as the antagonistic indicators and the similarity profile proved to be helpful in such conflicts. Thus beyond the application of HDT in the field of multicriteria decision aid (MCDA) the approach might be a helpful tool to mediate the whole decision process. 

The MCDA approach mainly relies on the estimate of the overall BR score in BR assessment, which does not accoimt for the uncertainties associated with sampling variation in the data for the benefit and risk endpoints. In addition, MCDA requires an explicit supply of weights for each criterion. Such weights are not easy to derive and are likely to differ among different decision makers. Stochastic multicriteria acceptability analysis (SMAA) was extended for BRA to deal with these limitations in MCDA (Tervonen et al. 2011). 

It is possible to terminate an MCDA early we can use it simply to place options before us in an unbiased way, leaving the final decision to policy makers (thus it operates as a multicriteria analysis, MCA). 

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See also in sourсe #XX -- [ , ]

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