Literature DB >> 19807438

Discrete choice experiments to measure consumer preferences for health and healthcare.

Rosalie Viney1, Emily Lancsar, Jordan Louviere.   

Abstract

To investigate the impact of health policies on individual well-being, estimate the value to society of new interventions or policies, or predict demand for healthcare, we need information about individuals' preferences. Economists usually use market-based data to analyze preferences, but such data are limited in the healthcare context. Discrete choice experiments are a potentially valuable tool for elicitation and analysis of preferences and thus, for economic analysis of health and health programs. This paper reviews the use of discrete choice experiments to measure consumers' preferences for health and healthcare. The paper provides an overview of the approach and discusses issues that arise when using discrete choice experiments to assess individuals' preferences for health and healthcare.

Year:  2002        PMID: 19807438     DOI: 10.1586/14737167.2.4.319

Source DB:  PubMed          Journal:  Expert Rev Pharmacoecon Outcomes Res        ISSN: 1473-7167            Impact factor:   2.217


  51 in total

1.  Discrete choice experiments in health care.

Authors:  Mandy Ryan
Journal:  BMJ       Date:  2004-02-14

2.  Things are Looking up Since We Started Listening to Patients: Trends in the Application of Conjoint Analysis in Health 1982-2007.

Authors:  John F P Bridges; Elizabeth T Kinter; Lillian Kidane; Rebekah R Heinzen; Colleen McCormick
Journal:  Patient       Date:  2008-12-01       Impact factor: 3.883

3.  Discrete choice experiment of smoking cessation behaviour in Japan.

Authors:  Rei Goto; Shuzo Nishimura; Takanori Ida
Journal:  Tob Control       Date:  2007-10       Impact factor: 7.552

4.  Sociocultural determinants of anticipated vaccine acceptance for acute watery diarrhea in early childhood in Katanga Province, Democratic Republic of Congo.

Authors:  Sonja Merten; Christian Schaetti; Cele Manianga; Bruno Lapika; Raymond Hutubessy; Claire-Lise Chaignat; Mitchell Weiss
Journal:  Am J Trop Med Hyg       Date:  2013-07-22       Impact factor: 2.345

5.  A closer look at decision and analyst error by including nonlinearities in discrete choice models: implications on willingness-to-pay estimates derived from discrete choice data in healthcare.

Authors:  Esther W de Bekker-Grob; John M Rose; Michiel C J Bliemer
Journal:  Pharmacoeconomics       Date:  2013-12       Impact factor: 4.981

6.  Treating patients with colon cancer liver metastasis: a nationwide analysis of therapeutic decision making.

Authors:  Hari Nathan; John F Bridges; David P Cosgrove; Luis A Diaz; Daniel A Laheru; Joseph M Herman; Richard D Schulick; Barish H Edil; Christopher L Wolfgang; Michael A Choti; Timothy M Pawlik
Journal:  Ann Surg Oncol       Date:  2012-08-09       Impact factor: 5.344

7.  Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software.

Authors:  Emily Lancsar; Denzil G Fiebig; Arne Risa Hole
Journal:  Pharmacoeconomics       Date:  2017-07       Impact factor: 4.981

8.  Quality versus quantity in end-of-life choices of cancer patients and support persons: a discrete choice experiment.

Authors:  Amy Waller; Rob Sanson-Fisher; Scott D Brown; Laura Wall; Justin Walsh
Journal:  Support Care Cancer       Date:  2018-05-03       Impact factor: 3.603

9.  Patient preferences and National Health Service costs: a cost-consequences analysis of cancer genetic services.

Authors:  Gethin L Griffith; Rhiannon Tudor Edwards; J Mark G Williams; Jonathon Gray; Val Morrison; Clare Wilkinson; Jim Turner; Barbara France; Paul Bennett
Journal:  Fam Cancer       Date:  2008-09-27       Impact factor: 2.375

10.  Eliciting preferences for priority setting in genetic testing: a pilot study comparing best-worst scaling and discrete-choice experiments.

Authors:  Franziska Severin; Jörg Schmidtke; Axel Mühlbacher; Wolf H Rogowski
Journal:  Eur J Hum Genet       Date:  2013-03-13       Impact factor: 4.246

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