Using Discrete Choice Experiments with Duration to Model EQ-5D-5L Health State Preferences: Testing Experimental Design Strategies

Mulhern, B; Bansback, N; Hole, AR; Tsuchiya, A

Using Discrete Choice Experiments with Duration to Model EQ-5D-5L Health State Preferences: Testing Experimental Design Strategies

Mulhern, B

Bansback, N Hole, AR Tsuchiya, A

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Publication Type:: Journal Article
Citation:: Medical Decision Making, 2017, 37 (3), pp. 285 - 297
Issue Date:: 2017-04-01

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Field	Value	Language
dc.contributor.author	Mulhern, B https://orcid.org/0000-0003-3656-8063	en_US
dc.contributor.author	Bansback, N	en_US
dc.contributor.author	Hole, AR	en_US
dc.contributor.author	Tsuchiya, A	en_US
dc.date.issued	2017-04-01	en_US
dc.identifier.citation	Medical Decision Making, 2017, 37 (3), pp. 285 - 297	en_US
dc.identifier.issn	0272-989X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/98662
dc.description.abstract	© The Author(s) 2016. Background: Discrete choice experiments incorporating duration can be used to derive health state values for EQ-5D-5L. Yet, methodological issues relating to the duration attribute and the optimal way to select health states remain. The aims of this study were to: test increasing the number of duration levels and choice sets where duration varies (aim 1); compare designs with zero and non-zero prior values (aim 2); and investigate a novel, two-stage design to incorporate prior values (aim 3). Methods: Informed by zero and non-zero prior values, two efficient designs were developed, each consisting of 120 EQ-5D-5L health profile pairs with one of six duration levels (aims 1 and 2). Another 120 health state pairs were selected, with one of six duration levels allocated in a second stage based on existing estimated utility of the states (aim 3). An online sample of 2,002 members of the UK general population completed 10 choice sets each. Differences across the regression coefficients from the three designs were assessed. Results: The zero prior value design produced a model with coefficients that were generally logically ordered, but the non-zero prior value design resulted in a set of less ordered coefficients where some differed significantly. The two-stage design resulted in ordered and significant coefficients. The non-zero prior value design may include more "difficult" choice sets, based on the proportions choosing each profile. Conclusions: There is some indication of compromised "respondent efficiency", suggesting that the use of non-zero prior values will not necessarily result in better overall precision. It is feasible to design discrete choice experiments in two stages by allocating duration values to EQ-5D-5L health state pairs based on estimates from prior studies.	en_US
dc.relation.ispartof	Medical Decision Making	en_US
dc.relation.isbasedon	10.1177/0272989X16670616	en_US
dc.subject.classification	Health Policy & Services	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Choice Behavior	en_US
dc.subject.mesh	Health Status	en_US
dc.subject.mesh	Quality-Adjusted Life Years	en_US
dc.subject.mesh	Quality of Life	en_US
dc.subject.mesh	Patient Preference	en_US
dc.subject.mesh	United Kingdom	en_US
dc.title	Using Discrete Choice Experiments with Duration to Model EQ-5D-5L Health State Preferences: Testing Experimental Design Strategies	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	37	en_US
utslib.for	140208 Health Economics	en_US
utslib.for	1117 Public Health and Health Services	en_US
utslib.for	1402 Applied Economics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Strength - CHERE - Centre for Health Economics Research and Evaluation
utslib.copyright.status	closed_access
pubs.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	37	en_US

Abstract:

© The Author(s) 2016. Background: Discrete choice experiments incorporating duration can be used to derive health state values for EQ-5D-5L. Yet, methodological issues relating to the duration attribute and the optimal way to select health states remain. The aims of this study were to: test increasing the number of duration levels and choice sets where duration varies (aim 1); compare designs with zero and non-zero prior values (aim 2); and investigate a novel, two-stage design to incorporate prior values (aim 3). Methods: Informed by zero and non-zero prior values, two efficient designs were developed, each consisting of 120 EQ-5D-5L health profile pairs with one of six duration levels (aims 1 and 2). Another 120 health state pairs were selected, with one of six duration levels allocated in a second stage based on existing estimated utility of the states (aim 3). An online sample of 2,002 members of the UK general population completed 10 choice sets each. Differences across the regression coefficients from the three designs were assessed. Results: The zero prior value design produced a model with coefficients that were generally logically ordered, but the non-zero prior value design resulted in a set of less ordered coefficients where some differed significantly. The two-stage design resulted in ordered and significant coefficients. The non-zero prior value design may include more "difficult" choice sets, based on the proportions choosing each profile. Conclusions: There is some indication of compromised "respondent efficiency", suggesting that the use of non-zero prior values will not necessarily result in better overall precision. It is feasible to design discrete choice experiments in two stages by allocating duration values to EQ-5D-5L health state pairs based on estimates from prior studies.

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http://hdl.handle.net/10453/98662