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Pharmacoeconomics. 2015 Mar;33(3):255-69. doi: 10.1007/s40273-014-0235-x.

Value-based reimbursement decisions for orphan drugs: a scoping review and decision framework.

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Department of Emergency Medicine, University of Alberta, 736 University Terrace, 8303 112 St, Edmonton, AB, T6G 2T4, Canada,



The rate of development of new orphan drugs continues to grow. As a result, reimbursing orphan drugs on an exceptional basis is increasingly difficult to sustain from a health system perspective. An understanding of the value that societies attach to providing orphan drugs at the expense of other health technologies is now recognised as an important input to policy debates.


The aim of this work was to scope the social value arguments that have been advanced relating to the reimbursement of orphan drugs, and to locate these within a coherent decision-making framework to aid reimbursement decisions in the presence of limited healthcare resources.


A scoping review of the peer reviewed and grey literature was undertaken, consisting of seven phases: (1) identifying the research question; (2) searching for relevant studies; (3) selecting studies; (4) charting, extracting and tabulating data; (5) analyzing data; (6) consulting relevant experts; and (7) presenting results. The points within decision processes where the identified value arguments would be incorporated were then located. This mapping was used to construct a framework characterising the distinct role of each value in informing decision making.


The scoping review identified 19 candidate decision factors, most of which can be characterised as either value-bearing or 'opportunity cost'-determining, and also a number of value propositions and pertinent sources of preference information. We were able to synthesize these into a coherent decision-making framework.


Our framework may be used to structure policy discussions and to aid transparency about the values underlying reimbursement decisions for orphan drugs. These values ought to be consistently applied to all technologies and populations affected by the decision.

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