Cited by 1,799Economic and Environmental ValuationHealth Systems, Economic Evaluations, Quality of LifeOptimal Experimental Design Methods

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Constructing Experimental Designs for Discrete-Choice Experiments: Report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force

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Reed Johnson, F., Lancsar, Emily, Marshall, Deborah, Kilambi, Vikram, Mühlbacher, Axel, Regier, Dean A., Bresnahan, Brian W., Kanninen, Barbara, Bridges, John F.P.·2013·Value in Health

DOI 10.1016/j.jval.2012.08.2223

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Abstract

Stated-preference methods are a class of evaluation techniques for studying the preferences of patients and other stakeholders. While these methods span a variety of techniques, conjoint-analysis methods-and particularly discrete-choice experiments (DCEs)-have become the most frequently applied approach in health care in recent years. Experimental design is an important stage in the development of such methods, but establishing a consensus on standards is hampered by lack of understanding of available techniques and software. This report builds on the previous ISPOR Conjoint Analysis Task Force Report: Conjoint Analysis Applications in Health-A Checklist: A Report of the ISPOR Good Research Practices for Conjoint Analysis Task Force. This report aims to assist researchers specifically in evaluating alternative approaches to experimental design, a difficult and important element of successful DCEs. While this report does not endorse any specific approach, it does provide a guide for choosing an approach that is appropriate for a particular study. In particular, it provides an overview of the role of experimental designs for the successful implementation of the DCE approach in health care studies, and it provides researchers with an introduction to constructing experimental designs on the basis of study objectives and the statistical model researchers have selected for the study. The report outlines the theoretical requirements for designs that identify choice-model preference parameters and summarizes and compares a number of available approaches for constructing experimental designs. The task-force leadership group met via bimonthly teleconferences and in person at ISPOR meetings in the United States and Europe. An international group of experimental-design experts was consulted during this process to discuss existing approaches for experimental design and to review the task force's draft reports. In addition, ISPOR members contributed to developing a consensus report by submitting written comments during the review process and oral comments during two forum presentations at the ISPOR 16th and 17th Annual International Meetings held in Baltimore (2011) and Washington, DC (2012).

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Ramezani, S., Rinne, T. E., Hasanzadeh, K., & Kyttä, M. (2019) · Transportation · doi:10.1007/s11116-019-10065-z · Cited by 46
Discrete Choice Experiments in Health State Valuation: A Systematic Review of Progress and New Trends
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Patient‐centered benefit–risk assessment in duchenne muscular dystrophy
Hollin, I. L., Peay, H. L., Apkon, S. D., & Bridges, J. F. P. (2016) · Muscle & Nerve · doi:10.1002/mus.25411 · Cited by 46
Self-citation
A cluster randomised trial of strategies to increase cervical screening uptake at first invitation (STRATEGIC)
Kitchener, H. C., Gittins, M., Rivero‐Arias, O., Tsiachristas, A., Cruickshank, M. E., Gray, A. M., Brabin, L., Torgerson, D. J., Crosbie, E. J., Sargent, A., et al. (2016) · Health Technology Assessment · doi:10.3310/hta20680 · Cited by 47
Choosing Video Instead of In-Clinic Consultations in Primary Care in Israel: Discrete Choice Experiment Among Key Stakeholders—Patients, Primary Care Physicians, and Policy Makers
Chudner, I., Drach‐Zahavy, A., & Karkabi, K. (2019) · Value in Health · doi:10.1016/j.jval.2019.05.001 · Cited by 45
The relative value of different QALY types
Lancsar, E., Gu, Y., Gyrd‐Hansen, D., Butler, J., Ratcliffe, J., Bulfone, L., & Donaldson, C. (2020) · Journal of Health Economics · doi:10.1016/j.jhealeco.2020.102303 · Cited by 51
Self-citation
Factors Driving Patient Preferences for Growth Hormone Deficiency (GHD) Injection Regimen and Injection Device Features: A Discrete Choice Experiment
McNamara, M., Turner‐Bowker, D. M., Westhead, H., Yaworsky, A., Palladino, A., Gross, H. J., Pleil, A. M., & Loftus, J. (2020) · Patient Preference and Adherence · doi:10.2147/ppa.s239196 · Cited by 46
Quantifying patient preferences for systemic atopic dermatitis treatments using a discrete-choice experiment
Boeri, M., Sutphin, J., Hauber, B., Cappelleri, J. C., Romero, W., & Bonaventura, M. D. (2020) · Journal of Dermatological Treatment · doi:10.1080/09546634.2020.1832185 · Cited by 46
“DCEs, however, are a well-established method for eliciting patient preferences for treatment features, and this study followed the applicable good practices for such study designs (30,31,33).”
Method
Vaccine preferences driving vaccine-decision making of different target groups: a systematic review of choice-based experiments
Diks, M. E., Hiligsmann, M., & van der Putten, I. M. (2021) · BMC Infectious Diseases · doi:10.1186/s12879-021-06398-9 · Cited by 48
“Guo, Zhang, Zhu, Wang & Shi [45] described this as “If you were actually offered the two vaccines above, which would you prefer to choose?”.”
BackgroundInfluential
Quantitative Benefit-Risk Assessment in Medical Product Decision Making: A Good Practices Report of an ISPOR Task Force.
Tervonen, T., Veldwijk, J., Payne, K., Ng, X.-Y., Levitan, B., Lackey, L., Marsh, K., Thokala, P., Pignatti, F., Donnelly, A. M., et al. (2023) · Value in Health · doi:10.1016/j.jval.2022.12.006 · Cited by 39
Eliciting community preferences for complementary micro health insurance: A discrete choice experiment in rural Malawi
Abiiro, G. A., Torbica, A., Kwalamasa, K., & Allegri, M. D. (2014) · Social Science & Medicine · doi:10.1016/j.socscimed.2014.09.021 · Cited by 45
Assessing Patient Preferences for Treatment Options and Process of Care in Inflammatory Bowel Disease: A Critical Review of Quantitative Data
Bewtra, M., & Johnson, F. R. (2013) · Patient · doi:10.1007/s40271-013-0031-2 · Cited by 45
Words or graphics to present a Discrete Choice Experiment: Does it matter?
Veldwijk, J., Lambooij, M., van Til, J. A., Groothuis‐Oudshoorn, C. G. M., Smit, H. A., & de Wit, G. A. (2015) · Patient Education and Counseling · doi:10.1016/j.pec.2015.06.002 · Cited by 45
Preferences for Pre-exposure Prophylaxis Service Delivery Among Female Sex Workers in Malawi: A Discrete Choice Experiment
Lancaster, K. E., Lungu, T., Bula, A. K., Shea, J., Shoben, A. B., Hosseinipour, M. C., Kohler, R. E., Hoffman, I., Go, V. F.-L., Golin, C. E., et al. (2019) · AIDS and Behavior · doi:10.1007/s10461-019-02705-3 · Cited by 45
Discrete choice experiments of pharmacy services: a systematic review
Vass, C., Gray, E., & Payne, K. (2015) · International Journal of Clinical Pharmacy · doi:10.1007/s11096-015-0221-1 · Cited by 44
Patient preferences for treatment of multiple sclerosis with disease-modifying therapies: a discrete choice experiment
Martinez, E., García‐Domínguez, J. M., Muñoz, D., Comellas, M., Gozalbo, I., Lizán, L., & Polanco, C. (2016) · Patient Preference and Adherence · doi:10.2147/ppa.s114619 · Cited by 44
A Systematic Review Comparing the Acceptability, Validity and Concordance of Discrete Choice Experiments and Best–Worst Scaling for Eliciting Preferences in Healthcare
Whitty, J. A., & Gonçalves, A. S. O. (2017) · Patient · doi:10.1007/s40271-017-0288-y · Cited by 44
“Whilst this supports the assertion that BWS is a more statistically efficient format [34], it does not suggest that BWS has greater response efficiency, which is also an important consideration for sample size and data quality [37].”
Background
Patient preferences for the delivery of cardiac rehabilitation
Boyde, M. S., Rankin, J., Whitty, J. A., Peters, R., Holliday, J., Baker, C., Hwang, R., Lynagh, D., & Korczyk, D. (2018) · Patient Education and Counseling · doi:10.1016/j.pec.2018.07.010 · Cited by 44
Patient and caregiver preferences for the potential benefits and risks of a seizure forecasting device: A best–worst scaling
Janse, S., Dumanis, S. B., Huwig, T., Hyman, S. R., Fureman, B. E., & Bridges, J. F. P. (2019) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2019.04.018 · Cited by 44
Self-citation
Financing electricity access in Africa: A choice experiment study of household investor preferences for renewable energy investments in Ghana
Menyeh, B. O. (2021) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2021.111132 · Cited by 45
Consumer understanding and evaluation of carbon-neutral electric vehicle charging services
Will, C., Lehmann, N., Baumgartner, N., Feurer, S., Jochem, P. E. P., & Fïchtner, W. (2022) · Applied Energy · doi:10.1016/j.apenergy.2022.118799 · Cited by 43
Effects of financial incentives on motivating physical activity among older adults: results from a discrete choice experiment
Farooqui, M. A., Tan, Y.-T., Bilger, M., & Finkelstein, E. A. (2014) · BMC Public Health · doi:10.1186/1471-2458-14-141 · Cited by 45
Designing Effective and Acceptable Road Pricing Schemes: Evidence from the Geneva Congestion Charge
Baranzini, A., Carattini, S., & Tesauro, L. (2021) · Environmental and Resource Economics · doi:10.1007/s10640-021-00564-y · Cited by 42
Using Discrete Choice Experiments to Inform the Benefit-Risk Assessment of Medicines: Are We Ready Yet?
Vass, C., & Payne, K. (2017) · PharmacoEconomics · doi:10.1007/s40273-017-0518-0 · Cited by 42
The impact of flavors, health risks, secondhand smoke and prices on young adults’ cigarette and e‐cigarette choices: a discrete choice experiment
Buckell, J., & Sindelar, J. L. (2019) · Addiction · doi:10.1111/add.14610 · Cited by 45
“The experiment is ‘labeled’, which is beneficial for survey realism and data quality [51,52].”
Background
Development of a Discrete-Choice Experiment (DCE) to Elicit Adolescent and Parent Preferences for Hypodontia Treatment
Barber, S., Bekker, H., Marti, J., Pavitt, S. H., Khambay, B., & Meads, D. M. (2018) · Patient · doi:10.1007/s40271-018-0338-0 · Cited by 44
U.K. Intensivists’ Preferences for Patient Admission to ICU: Evidence From a Choice Experiment
Bassford, C. R., Krucien, N., Ryan, M., Griffiths, F. E., Svantesson, M., Fritz, Z. B. M., Perkins, G. D., Quinton, S., & Slowther, A. (2019) · Critical Care Medicine · doi:10.1097/ccm.0000000000003903 · Cited by 42
Demand for Precision Medicine: A Discrete-Choice Experiment and External Validation Study
Regier, D. A., Veenstra, D. L., Basu, A., & Carlson, J. J. (2019) · PharmacoEconomics · doi:10.1007/s40273-019-00834-0 · Cited by 42
Self-citation
Age at Diagnosis and Patient Preferences for Treatment Outcomes in AML: A Discrete Choice Experiment to Explore Meaningful Benefits
Richardson, D. R., Crossnohere, N. L., Seo, J., Estey, E. H., O’Donoghue, B., Smith, B. D., & Bridges, J. F. P. (2020) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-19-1277 · Cited by 42
“This was done in accordance with bestpractices as includingOS often results in dominance andmay critically undermine the validity of the DCE (8, 20, 21).”
MethodSelf-citation
Patient Preferences for Injectable Treatments for Multiple Sclerosis in the United States: A Discrete-Choice Experiment
Poulos, C. M., Kinter, E. T., Yang, J., Bridges, J. F. P., Posner, J., & Reder, A. T. (2015) · Patient · doi:10.1007/s40271-015-0136-x · Cited by 42
Self-citation
A Survey of Patient Preferences for Oral Antihyperglycemic Therapy in Patients with Type 2 Diabetes Mellitus
Hauber, B., Tunceli, K., Yang, J., Gantz, I., Brodovicz, K. G., Alexander, C. M., Davies, M. J., & Radican, L. (2015) · Diabetes Therapy · doi:10.1007/s13300-015-0094-2 · Cited by 40
The value of quantitative patient preferences in regulatory benefit-risk assessment
Egbrink, M. O., & IJzerman, M. J. (2014) · Journal of Market Access & Health Policy · doi:10.3402/jmahp.v2.22761 · Cited by 40
Using blocked fractional factorial designs to construct discrete choice experiments for healthcare studies
Jaynes, J., Wong, W. K., & Xu, H. (2016) · Statistics in Medicine · doi:10.1002/sim.6882 · Cited by 40
“A subject may not be able to assess pain severity without knowing how long the pain will last and may not be able to assess pain duration without knowing how severe the pain is during a specified period [5].”
Background
Comparing internet and face-to-face surveys as methods for eliciting preferences for social care-related quality of life: evidence from England using the ASCOT service user measure
Saloniki, E., Malley, J., Burge, P., Lu, H., Batchelder, L., Linnosmaa, I., Trukeschitz, B., & Forder, J. (2019) · Quality of Life Research · doi:10.1007/s11136-019-02172-2 · Cited by 40
What can discrete choice experiments do for you?
Cleland, J., Porteous, T., & Skåtun, D. (2018) · Medical Education · doi:10.1111/medu.13657 · Cited by 40
The evolving role of patient preference studies in health-care decision-making, from clinical drug development to clinical care management
Jackson, Y., Janssen, E. M., Fischer, R. A., Beaverson, K. L., Loftus, J., Betteridge, K., Rhoten, S. E., Flood, E. M., & Lundie, M. J. (2019) · Expert Review of Pharmacoeconomics & Outcomes Research · doi:10.1080/14737167.2019.1612242 · Cited by 40
“However, stated-preference methods have the advantage of measuring preferences in a controlled experimental setting and can more easily control the decisionmaking scenario compared to revealed-preference studies [20].”
Background
Personalized public health: An implementation research agenda for the HIV response and beyond
Geng, E., Holmes, C. B., Moshabela, M., Sikazwe, I. T., & Petersen, M. L. (2019) · PLoS Medicine · doi:10.1371/journal.pmed.1003020 · Cited by 38

Authors: Reed Johnson, F., Lancsar, E., Marshall, D., Kilambi, V., Mühlbacher, A., Regier, D. A., Bresnahan, B. W., Kanninen, B., & Bridges, J. F. P.
Affiliations: Monash University (AU)
University of Calgary (CA)
RTI Health Solutions (US)
Duke University (US)
BC Cancer Agency (CA)
University of Washington (US)
Johns Hopkins University (US)
ORCID: Lancsar, Emily
Marshall, Deborah
Kilambi, Vikram
Mühlbacher, Axel
Regier, Dean A.
Bridges, John F.P.
Venue: Value in Health
Publisher: Elsevier BV
Published: 2013-01
Volume: 16
Issue: 1
Pages: 3-13
ISSN: 1098-3015 (ISSN-L)
DOI: 10.1016/j.jval.2012.08.2223
OpenAlex: W2159936838
Cited by: 1,799
References: 51
Citations by year: 2026: 158 · 2025: 181 · 2024: 213 · 2023: 162 · 2022: 190 · 2021: 186 · 2020: 150 · 2019: 117 · 2018: 109 · 2017: 109 · 2016: 99 · 2015: 56 · 2014: 50 · 2013: 15
FWCI: 171.60
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/open-access/userlicense/1.0/ (vor, 365 d)
Locations: Value in Health (publishedVersion)
PubMed (publishedVersion)
Topics: Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic and Environmental Valuation
Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
Keywords: discrete choice experiment, experimental design, stated preference methods, conjoint analysis, health care preferences, choice models, good scientific practice
MeSH terms: Choice Behavior, Delivery of Health Care, Humans, International Cooperation, Research Design, Models, Statistical, Patient Preference

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Constructing Experimental Designs for Discrete-Choice Experiments: Report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force

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