Literature DB >> 21205401

A discrete choice experiment investigating preferences for funding drugs used to treat orphan diseases: an exploratory study.

Emmanouil Mentzakis1, Patricia Stefanowska, Jeremiah Hurley.   

Abstract

Policy debate about funding criteria for drugs used to treat rare, orphan diseases is gaining prominence. This study presents evidence from a discrete choice experiment using a convenience sample of university students to investigate individual preferences regarding public funding for drugs used to treat rare diseases and common diseases. This pilot study finds that: other things equal, the respondents do not prefer to have the government spend more for drugs used to treat rare diseases; that respondents are not willing to pay more per life year gained for a rare disease than a common disease; and that respondents weigh relevant attributes of the coverage decisions (e.g. costs, disease severity and treatment effectiveness) similarly for both rare and common diseases. The results confirm the importance of severity and treatment effectiveness in preferences for public funding. Although this is the first study of its kind, the results send a cautionary message regarding the special treatment of orphan drugs in coverage decision-making.

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Year:  2010        PMID: 21205401     DOI: 10.1017/S1744133110000344

Source DB:  PubMed          Journal:  Health Econ Policy Law        ISSN: 1744-1331


  16 in total

1.  Challenges in measuring the societal value of orphan drugs: insights from a canadian stated preference survey.

Authors:  Nick Dragojlovic; Shirin Rizzardo; Nick Bansback; Craig Mitton; Carlo A Marra; Larry D Lynd
Journal:  Patient       Date:  2015-02       Impact factor: 3.883

2.  Using Latent Class Analysis to Model Preference Heterogeneity in Health: A Systematic Review.

Authors:  Mo Zhou; Winter Maxwell Thayer; John F P Bridges
Journal:  Pharmacoeconomics       Date:  2018-02       Impact factor: 4.981

Review 3.  A systematic review of stated preference studies reporting public preferences for healthcare priority setting.

Authors:  Jennifer A Whitty; Emily Lancsar; Kylie Rixon; Xanthe Golenko; Julie Ratcliffe
Journal:  Patient       Date:  2014       Impact factor: 3.883

Review 4.  Discrete choice experiments in health economics: a review of the literature.

Authors:  Michael D Clark; Domino Determann; Stavros Petrou; Domenico Moro; Esther W de Bekker-Grob
Journal:  Pharmacoeconomics       Date:  2014-09       Impact factor: 4.981

Review 5.  The Equitable Implementation of Cystic Fibrosis Personalized Medicines in Canada.

Authors:  Genevieve Shemie; Minh Thu Nguyen; John Wallenburg; Felix Ratjen; Bartha Maria Knoppers
Journal:  J Pers Med       Date:  2021-05-07

Review 6.  A systematic review of moral reasons on orphan drug reimbursement.

Authors:  Bettina M Zimmermann; Johanna Eichinger; Matthias R Baumgartner
Journal:  Orphanet J Rare Dis       Date:  2021-06-30       Impact factor: 4.123

7.  Principles for consistent value assessment and sustainable funding of orphan drugs in Europe.

Authors:  Laura Gutierrez; Julien Patris; Adam Hutchings; Warren Cowell
Journal:  Orphanet J Rare Dis       Date:  2015-05-03       Impact factor: 4.123

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

Authors:  Mike Paulden; Tania Stafinski; Devidas Menon; Christopher McCabe
Journal:  Pharmacoeconomics       Date:  2015-03       Impact factor: 4.981

9.  Eliciting the public preferences for pharmaceutical subsidy in Iran: a discrete choice experiment study.

Authors:  Mansoor Delpasand; Alireza Olyaaeemanesh; Ebrahim Jaafaripooyan; Akbar Abdollahiasl; Majid Davari; Ali Kazemi Karyani
Journal:  J Pharm Policy Pract       Date:  2021-07-13

10.  Can the EVIDEM Framework Tackle Issues Raised by Evaluating Treatments for Rare Diseases: Analysis of Issues and Policies, and Context-Specific Adaptation.

Authors:  Monika Wagner; Hanane Khoury; Jacob Willet; Donna Rindress; Mireille Goetghebeur
Journal:  Pharmacoeconomics       Date:  2016-03       Impact factor: 4.981

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