scholarly journals Value-based decision-making for orphan drugs with multiple criteria decision analysis: burosumab for the treatment of X-linked hypophosphatemia

Author(s):  
Björn Vandewalle ◽  
Miguel Amorim ◽  
Diogo Ramos ◽  
Sofia Azevedo ◽  
Inês Alves ◽  
...  
2017 ◽  
Vol 23 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Ting-Yu CHEN

The theory of interval type-2 fuzzy sets provides an intuitive and computationally feasible method of addressing uncertain and ambiguous information in decision-making fields. This paper aims to develop a prioritised interval type-2 fuzzy aggregation operator and apply it to multiple criteria decision analysis with prioritised criteria. This paper considers situations in which a relationship between the criteria exists such that a lack of satisfaction by the higher priority criteria cannot be readily compensated by the satisfaction of lower priority criteria. This paper introduces the developed prioritised interval type-2 fuzzy aggregation operator to address the problem of criteria aggregation in this environment. To demonstrate the feasibility of the proposed operator, this paper provides a multiple criteria decision-making method that uses the prioritised interval type-2 fuzzy aggregation operator, and the method is illustrated with a practical application to landfill site selection.


2020 ◽  
Vol 13 (4) ◽  
pp. 850-874
Author(s):  
Breno Barros Telles do Carmo ◽  
Manuele Margni ◽  
Pierre Baptiste

Purpose – Life cycle sustainability assessment (LCSA) provides useful and comprehensive information on product system performance. However, it poses several challenges for decision-making process due to (i) multidimensional indicators, (ii) conflicting objectives and (iii) uncertainty associated with the performance assessment. This research proposes an approach able to account uncertain life cycle sustainability performances through multiple criteria decision analysis (MCDA) process to support decision-making.Design/methodology/approach – Our method is structured in three phases: i) assessing the uncertainty of LCSA performances, ii) propagating LCSA uncertainty into MCDA methods and iii) interpreting the stochastic results. The approach is applied on an illustrative case study, ranking four alternatives to biodiesel supply.Findings –The recommendation generated by this approach provides an information about the confidence the decision maker can have in a given result (ranking of solutions) under the form of a probability, providing a better knowledge of the risk (in this case due to the uncertainty of the preferred solution). As such, stochastic results, if appropriately interpreted, provide a measure of the robustness of the rankings generated by MCDA methods, overcoming the limitation of the overconfidence of deterministic rankings.Originality/value – The fundamental contributions of this paper are to (i) integrate LCSA uncertainty into decision-making processes through MCDA approach; (ii) provide a sensitivity analysis about the MCDA method choice, (iii) support decision-makers’ preference choices through a transparent elicitation process and (iv) provide a practical decision-making platform that accounts simultaneously uncertain LCSA performances with stakeholders’ value judgments.


2016 ◽  
Vol 17 (12) ◽  
Author(s):  
Efat Mohamadi ◽  
Seyed Mousa Tabatabaei ◽  
Alireza Olyaeemanesh ◽  
Seyede Fateme Sagha ◽  
Marziyeh Zanganeh ◽  
...  

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1785 ◽  
Author(s):  
Otto Chen ◽  
Dawei Han

Multiple criteria decision analysis (MCDA) methods have shown advantages in supporting decision-making with problems that confront conflicting objectives. However, current applications to complex environmental problems featuring the dynamic social sphere, particularly problems involving cultural heritage and nature, have yet to substantially reflect this. The dynamic social sphere reflects the demand for scenario forecasting in decision-making support. This knowledge gap has not been addressed sufficiently in MCDA research. A participatory MCDA method is hence proposed as a merger with Contingent Valuation Method (CVM) as the scenario forecasting. The MCDA is then carried out to tackle a complex environmental problem caused by traditional food production in a historic town, Daxi in Taiwan. The result reveals a remarkable willingness to support this issue of a historically significant industry causing detriment to environment (with WTP estimate of 128,700,000 USD from the public) and suggests a plan that applies multiple policy instruments rather than following a potentially adverse polluter-pays principle. This manifests the authors’ argument that recognition of heritage significance has dramatically affected selection of policy instruments and provides a critical recommendation to the local government which has struggled to find solutions. The proposed MCDA also highlights its participatory aspect for addressing issues involving cultural heritage, supported by several key steps, in particular the intervention-impact value tree building, the scenario forecasting and the sensitivity analysis.


2020 ◽  
Vol 40 (4) ◽  
pp. 438-447
Author(s):  
Vusal Babashov ◽  
Sarah Ben Amor ◽  
Gilles Reinhardt

Background. Reviewing drugs to determine coverage or reimbursement level is a complex process that involves significant time and expertise. Review boards gather evidence from the submission provided, input from clinicians and patients, and results of clinical and economic reviews. This information consists of assessments on multiple criteria that often conflict with one another. Multiple-criteria decision analysis (MCDA) includes methods to address complex decision making problems with conflicting objectives and criteria. We propose an MCDA approach that infers a utility model based on reviews of previously submitted drugs. Methods. We use a recent extension of the UTilitiés Additives DIScriminantes approach, UTADISGMS. This disaggregation approach deconstructs a portfolio of elements such as a set of drugs that have been reviewed and for which a decision has been made. It derives global and marginal utility functions that are consistent with the preferences exhibited by the review boards in their recommendations. We apply the method to oncology drugs reviewed in Canada between 2011 and 2017. We also illustrate how to conduct scenario analyses and predict the coverage decisions for new drugs. Results. Applying the method yields a utility value for each submission along with a set of thresholds that partition the utility values based on the submission outcomes. Scenario analyses illustrate the predictive ability of the method. Conclusion. Preference disaggregation is an indirect way of eliciting an additive global utility value function. It requires less of a cognitive effort from the decision making bodies because it infers preferences from the data rather than relying on direct assessments of model parameters. We illustrate how it can be applied to validate existing decisions and to predict the recommendation of a new drug.


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