Evaluating Drugs for Rare Diseases (DRDs) for the purpose of reimbursement
and beyond represents a tremendous challenge for most health
care priorities. A consensus is set about the irrelevance of cost e ectiveness
analysis to evaluate such drugs. The appeal for multi criteria decision aid
models seems reasonable as the evaluation of DRDs is indeed multifaceted.
However, the application of MCDA for the purpose of evaluating DRDs is yet
primitive and simplistic. The present work tries to tackle the issue of evaluating
DRDs from a decision maker angle by adopting an innovative robust
ordinal regression MCDA method, UTADIS-GMS, that helps the decision
maker discern between the DRDs based on their multi criteria value.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/35067 |
| Date | January 2016 |
| Creators | Naili, Abdallah |
| Contributors | Ben Amor, Sarah |
| Publisher | Université d'Ottawa / University of Ottawa |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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