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A novel design process for selection of attributes for inclusion in discrete choice experiments: case study exploring variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke

BACKGROUND: A discrete choice experiment (DCE) is a method used to elicit participants’ preferences and the relative importance of different attributes and levels within a decision-making process. DCEs have become popular in healthcare; however, approaches to identify the attributes/levels influenci...

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Autores principales: De Brún, Aoife, Flynn, Darren, Ternent, Laura, Price, Christopher I., Rodgers, Helen, Ford, Gary A., Rudd, Matthew, Lancsar, Emily, Simpson, Stephen, Teah, John, Thomson, Richard G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6013945/
https://www.ncbi.nlm.nih.gov/pubmed/29929523
http://dx.doi.org/10.1186/s12913-018-3305-5
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author De Brún, Aoife
Flynn, Darren
Ternent, Laura
Price, Christopher I.
Rodgers, Helen
Ford, Gary A.
Rudd, Matthew
Lancsar, Emily
Simpson, Stephen
Teah, John
Thomson, Richard G.
author_facet De Brún, Aoife
Flynn, Darren
Ternent, Laura
Price, Christopher I.
Rodgers, Helen
Ford, Gary A.
Rudd, Matthew
Lancsar, Emily
Simpson, Stephen
Teah, John
Thomson, Richard G.
author_sort De Brún, Aoife
collection PubMed
description BACKGROUND: A discrete choice experiment (DCE) is a method used to elicit participants’ preferences and the relative importance of different attributes and levels within a decision-making process. DCEs have become popular in healthcare; however, approaches to identify the attributes/levels influencing a decision of interest and to selection methods for their inclusion in a DCE are under-reported. Our objectives were: to explore the development process used to select/present attributes/levels from the identified range that may be influential; to describe a systematic and rigorous development process for design of a DCE in the context of thrombolytic therapy for acute stroke; and, to discuss the advantages of our five-stage approach to enhance current guidance for developing DCEs. METHODS: A five-stage DCE development process was undertaken. Methods employed included literature review, qualitative analysis of interview and ethnographic data, expert panel discussions, a quantitative structured prioritisation (ranking) exercise and pilot testing of the DCE using a ‘think aloud’ approach. RESULTS: The five-stage process reported helped to reduce the list of 22 initial patient-related factors to a final set of nine variable factors and six fixed factors for inclusion in a testable DCE using a vignette model of presentation. CONCLUSIONS: In order for the data and conclusions generated by DCEs to be deemed valid, it is crucial that the methods of design and development are documented and reported. This paper has detailed a rigorous and systematic approach to DCE development which may be useful to researchers seeking to establish methods for reducing and prioritising attributes for inclusion in future DCEs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12913-018-3305-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-60139452018-07-05 A novel design process for selection of attributes for inclusion in discrete choice experiments: case study exploring variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke De Brún, Aoife Flynn, Darren Ternent, Laura Price, Christopher I. Rodgers, Helen Ford, Gary A. Rudd, Matthew Lancsar, Emily Simpson, Stephen Teah, John Thomson, Richard G. BMC Health Serv Res Technical Advance BACKGROUND: A discrete choice experiment (DCE) is a method used to elicit participants’ preferences and the relative importance of different attributes and levels within a decision-making process. DCEs have become popular in healthcare; however, approaches to identify the attributes/levels influencing a decision of interest and to selection methods for their inclusion in a DCE are under-reported. Our objectives were: to explore the development process used to select/present attributes/levels from the identified range that may be influential; to describe a systematic and rigorous development process for design of a DCE in the context of thrombolytic therapy for acute stroke; and, to discuss the advantages of our five-stage approach to enhance current guidance for developing DCEs. METHODS: A five-stage DCE development process was undertaken. Methods employed included literature review, qualitative analysis of interview and ethnographic data, expert panel discussions, a quantitative structured prioritisation (ranking) exercise and pilot testing of the DCE using a ‘think aloud’ approach. RESULTS: The five-stage process reported helped to reduce the list of 22 initial patient-related factors to a final set of nine variable factors and six fixed factors for inclusion in a testable DCE using a vignette model of presentation. CONCLUSIONS: In order for the data and conclusions generated by DCEs to be deemed valid, it is crucial that the methods of design and development are documented and reported. This paper has detailed a rigorous and systematic approach to DCE development which may be useful to researchers seeking to establish methods for reducing and prioritising attributes for inclusion in future DCEs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12913-018-3305-5) contains supplementary material, which is available to authorized users. BioMed Central 2018-06-22 /pmc/articles/PMC6013945/ /pubmed/29929523 http://dx.doi.org/10.1186/s12913-018-3305-5 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Technical Advance
De Brún, Aoife
Flynn, Darren
Ternent, Laura
Price, Christopher I.
Rodgers, Helen
Ford, Gary A.
Rudd, Matthew
Lancsar, Emily
Simpson, Stephen
Teah, John
Thomson, Richard G.
A novel design process for selection of attributes for inclusion in discrete choice experiments: case study exploring variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke
title A novel design process for selection of attributes for inclusion in discrete choice experiments: case study exploring variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke
title_full A novel design process for selection of attributes for inclusion in discrete choice experiments: case study exploring variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke
title_fullStr A novel design process for selection of attributes for inclusion in discrete choice experiments: case study exploring variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke
title_full_unstemmed A novel design process for selection of attributes for inclusion in discrete choice experiments: case study exploring variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke
title_short A novel design process for selection of attributes for inclusion in discrete choice experiments: case study exploring variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke
title_sort novel design process for selection of attributes for inclusion in discrete choice experiments: case study exploring variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke
topic Technical Advance
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6013945/
https://www.ncbi.nlm.nih.gov/pubmed/29929523
http://dx.doi.org/10.1186/s12913-018-3305-5
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