scholarly journals Using a stated preference discrete choice experiment to assess societal value from the perspective of patients with rare diseases in Italy

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Julio López-Bastida ◽  
Juan Manuel Ramos-Goñi ◽  
Isaac Aranda-Reneo ◽  
Domenica Taruscio ◽  
Armando Magrelli ◽  
...  
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Rare Diseases ◽  
Choice Experiment ◽  
Stated Preference ◽  
Societal Value

Using a stated preference discrete choice experiment to assess societal value from the perspective of decision-makers in Europe. Does it work for rare diseases?

Health Policy ◽  
2019 ◽  
Vol 123 (2) ◽  
pp. 152-158 ◽  
Author(s):  
J. López-Bastida ◽  
J.M. Ramos-Goñi ◽  
I. Aranda-Reneo ◽  
M. Trapero-Bertran ◽  
P. Kanavos ◽  
...  
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Rare Diseases ◽  
Choice Experiment ◽  
Stated Preference ◽  
Decision Makers ◽  
Societal Value

scholarly journals Understanding uptake of digital health products: Methodology tutorial for a Discrete Choice Experiment using a Bayesian efficient design (Preprint)

2021 ◽  
Author(s):  
Dorothy Szinay ◽  
Rory Cameron ◽  
Felix Naughton ◽  
Jennifer A. Whitty ◽  
Jamie Brown ◽  
...  
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Stated Preference ◽  
Digital Health ◽  
Revealed Preferences ◽  
Quantitative Methodology ◽  
Efficient Design ◽  
Trade Offs ◽  
Health Products

UNSTRUCTURED Understanding the preferences of potential users of digital health products is beneficial for digital health policy and planning. Stated preference methods could help elicit individuals’ preferences in the absence of observational data. A discrete choice experiment (DCE) is a commonly used stated preference method; a quantitative methodology that argues that individuals make trade-offs when engaging in a decision by choosing an alternative of a product or service that offers the greatest utility, or benefit. This methodology is widely used in health economics in situations where revealed preferences are difficult to collect but is much less used in the field of digital health. This article outlines the stages involved in developing a discrete choice experiment. As a case study, it uses the application of a DCE for revealing preferences in targeting the uptake of smoking cessation apps. It describes the establishment of attributes, the construction of choice tasks of two or more alternatives, and the development of the experimental design. This tutorial offers a guide for researchers with no prior knowledge of this research technique.

scholarly journals Understanding Midwives’ Preferences for Providing Information About Newborn Bloodspot Screening

2018 ◽  
Vol 3 (1) ◽  
pp. 238146831774617 ◽  
Author(s):  
Stuart James Wright ◽  
Fiona Ulph ◽  
Tina Lavender ◽  
Nimarta Dharni ◽  
Katherine Payne
Keyword(s):  
Conjoint Analysis ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Screening Program ◽  
Stated Preference ◽  
Information Provision ◽  
Stated Preference Survey ◽  
Newborn Bloodspot Screening ◽  
Types Of Information

Background: Understanding preferences for information provision in the context of health care service provision is challenging because of the number of potential attributes that may influence preferences. This study aimed to identify midwives’ preferences for the process and outcomes of information provision in an expanded national newborn bloodspot screening program. Design: A sample of practicing midwives completed a hybrid-stated preference survey including a conjoint analysis (CA) and discrete choice experiment to quantify preferences for the types of, and way in which, information should be provided in a newborn bloodspot screening program. Six conjoint analysis questions captured the impact of different types of information on parents’ ability to make a decision, and 10 discrete choice experiment questions identified preferences for four process attributes (including parents’ ability to make a decision). Results: Midwives employed by the UK National Health Service (n = 134) completed the survey. All types of information content were perceived to improve parents’ ability to make a decision except for the possibility of false-positive results. Late pregnancy was seen to be the best time to provide information, followed by day 3 postbirth. Information before 20 weeks of pregnancy was viewed as reducing parents’ ability to make a decision. Midwives preferred information to be provided by an individual discussion and did not think parents should receive information on the Internet. Conclusion: A hybrid stated preference survey design identified that a wide variety of information should be provided to maximize parents’ ability to make a decision ideally provided late in pregnancy or on day 3 postbirth.

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

2010 ◽  
Vol 6 (3) ◽  
pp. 405-433 ◽  
Author(s):  
Emmanouil Mentzakis ◽  
Patricia Stefanowska ◽  
Jeremiah Hurley
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Rare Diseases ◽  
Choice Experiment ◽  
Treatment Effectiveness ◽  
Public Funding ◽  
Common Disease ◽  
Orphan Diseases ◽  
Convenience Sample ◽  
Common Diseases

AbstractPolicy 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.

A query theory account of a discrete choice experiment under oath

2019 ◽  
Vol 47 (3) ◽  
pp. 1133-1172
Author(s):  
Nathan P Kemper ◽  
Jennie S Popp ◽  
Rodolfo M Nayga
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Stated Preference ◽  
Choice Experiments ◽  
Hypothetical Bias ◽  
Discrete Choice Experiments ◽  
Thought Processes ◽  
Stated Preference Methods ◽  
Ex Ante

Abstract One limitation of stated-preference methods is the formation of hypothetical bias. To address this, the honesty oath has been used as an ex ante technique to reduce hypothetical bias. Our study provides a query account of the honesty oath in a discrete-choice experiment setting by using Query Theory to examine the mechanism behind the effectiveness of the honesty oath. Our results show that the honesty oath can change the content and order of queries; potentially reducing hypothetical bias in discrete choice experiments. The study suggests the potential usefulness of Query Theory in examining thought processes of respondents in valuation studies.

scholarly journals Stay-at-home orders and the willingness to stay home during the COVID-19 pandemic: A stated-preference discrete choice experiment

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253910
Author(s):  
Liqing Li ◽  
Dede Long ◽  
Mani Rouhi Rad ◽  
Matthew R. Sloggy
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Local Governments ◽  
Choice Experiment ◽  
Stated Preference ◽  
Related Factors ◽  
Work From Home ◽  
Trade Offs ◽  
State And Local ◽  
At Home

The spread of COVID-19 in the Spring of 2020 prompted state and local governments to implement a variety of policies, including stay-at-home (SAH) orders and mandatory mask requirements, aimed at reducing the infection rate and the severity of the pandemic’s impact. We implement a discrete choice experiment survey in three major U.S. States—California, Georgia, and Illinois—to empirically quantify individuals’ willingness to stay (WTS) home, measured as the number of weeks of a potential new SAH order, to prevent the spread of the COVID-19 disease and explore factors leading to their heterogeneous WTS. Our results demonstrate broad support for statewide mask mandates. In addition, the estimate of WTS to lower new positive cases is quite large, approximately five and half weeks, even though staying home lowers utility. We also find that individuals recognize the trade-offs between case reduction and economic slowdown stemming from SAH orders when they decide to stay home or not. Finally, pandemic related factors such as age, ability to work from home, and unemployment status are the main drivers of the heterogeneity in individuals’ WTS.

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