Literature DB >> 27712704

Measuring High-Risk Patients' Preferences for Pharmacogenetic Testing to Reduce Severe Adverse Drug Reaction: A Discrete Choice Experiment.

Di Dong1, Semra Ozdemir2, Yong Mong Bee3, Sue-Anne Toh4, Marcel Bilger2, Eric Finkelstein5.   

Abstract

OBJECTIVES: To investigate patient preferences and willingness to pay (WTP) for a genetic test that can reduce the risk of life-threatening adverse drug reactions (ADRs). We hypothesize that test features (risk of developing the adverse reaction with and without testing, test cost, and treatment cost) and the choice context (physician recommendation and the most common choice made by peer patients) will influence choices.
METHODS: A discrete choice experiment was conducted in which 189 patients at high risk for gout were asked to choose between treatment options that varied along key attributes. A latent class logit model was used to analyze the choice data and test the hypotheses.
RESULTS: We identified two classes of patients: the risk-averse class and the cost-conscious class. The WTP to reduce the risk of life-threatening ADRs from 1 out of 600 to 1 out of 1 million was SGD1215 in the risk-averse class. In contrast, in the cost-conscious class, the WTP was insensitive to the extent of risk reduction. Overall, the predicted take-up rate for the test is 65% at a price of SGD400. If the test was recommended by a physician or was chosen by most of the patients, the take-up rate for the test would increase by 8.5 and 1.5 percentage points, respectively.
CONCLUSIONS: There is a potentially large demand for genetic tests that could reduce the risk of life-threatening ADRs. Physician recommendations and providing information on the choices of others are powerful influences on demand, even more so than moderate price reductions.
Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  discrete choice experiment; patients’ preferences; pharmacogenetics; willingness to pay

Mesh:

Year:  2016        PMID: 27712704     DOI: 10.1016/j.jval.2016.03.1837

Source DB:  PubMed          Journal:  Value Health        ISSN: 1098-3015            Impact factor:   5.725


  9 in total

1.  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

2.  Assessing feasibility of delivering pharmacogenetic testing in a community pharmacy setting.

Authors:  Susanne B Haga; Jivan Moaddeb; Rachel Mills; Deepak Voora
Journal:  Pharmacogenomics       Date:  2017-02-22       Impact factor: 2.533

3.  Perceived fairness of direct-to-consumer genetic testing business models.

Authors:  Philipp A Toussaint; Scott Thiebes; Manuel Schmidt-Kraepelin; Ali Sunyaev
Journal:  Electron Mark       Date:  2022-07-18

4.  A Systematic Review of Discrete Choice Experiments and Conjoint Analysis on Genetic Testing.

Authors:  Semra Ozdemir; Jia Jia Lee; Isha Chaudhry; Remee Rose Quintana Ocampo
Journal:  Patient       Date:  2021-06-04       Impact factor: 3.883

5.  Predicted patient demand for a new delivery system for glaucoma medicine.

Authors:  Semra Ozdemir; Tina T Wong; Robert Rand Allingham; Eric A Finkelstein
Journal:  Medicine (Baltimore)       Date:  2017-04       Impact factor: 1.889

6.  Women's preferences, willingness-to-pay, and predicted uptake for single-nucleotide polymorphism gene testing to guide personalized breast cancer screening strategies: a discrete choice experiment.

Authors:  Xin Yi Wong; Catharina Gm Groothuis-Oudshoorn; Chuen Seng Tan; Janine A van Til; Mikael Hartman; Kok Joon Chong; Maarten J IJzerman; Hwee-Lin Wee
Journal:  Patient Prefer Adherence       Date:  2018-09-18       Impact factor: 2.711

7.  Discrete Choice Experiments in Health Economics: Past, Present and Future.

Authors:  Vikas Soekhai; Esther W de Bekker-Grob; Alan R Ellis; Caroline M Vass
Journal:  Pharmacoeconomics       Date:  2019-02       Impact factor: 4.981

8.  Pharmacogenomic Testing In Pediatrics: Navigating The Ethical, Social, And Legal Challenges.

Authors:  Susanne B Haga
Journal:  Pharmgenomics Pers Med       Date:  2019-10-14

9.  Physicians' preferences and willingness to pay for artificial intelligence-based assistance tools: a discrete choice experiment among german radiologists.

Authors:  Philip von Wedel; Christian Hagist
Journal:  BMC Health Serv Res       Date:  2022-03-26       Impact factor: 2.655

  9 in total

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