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01.12.2018 | Technical advance | Ausgabe 1/2018 Open Access

BMC Health Services Research 1/2018

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

Zeitschrift:
BMC Health Services Research > Ausgabe 1/2018
Autoren:
Aoife De Brún, Darren Flynn, Laura Ternent, Christopher I. Price, Helen Rodgers, Gary A. Ford, Matthew Rudd, Emily Lancsar, Stephen Simpson, John Teah, Richard G. Thomson
Wichtige Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s12913-018-3305-5) contains supplementary material, which is available to authorized users.

Abstract

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.
Zusatzmaterial
Additional file 1: On-line structured prioritisation exercise (SPE). Full survey used to collect data. (DOCX 42 kb)
12913_2018_3305_MOESM1_ESM.docx
Additional file 2: DCE pilot testing protocol. Interview schedule for cognitive interviewing and pilot testing of DCE. (DOCX 18 kb)
12913_2018_3305_MOESM2_ESM.docx
Additional file 3: Stage 3 (Phase 1): Results of on-line survey (SPE). Table presenting results of SPE online survey. (DOCX 22 kb)
12913_2018_3305_MOESM3_ESM.docx
Additional file 4: Operational definitions for variable attribute levels in the DCE. Table presenting definitions used for attribute levels in the DCE. (DOCX 13 kb)
12913_2018_3305_MOESM4_ESM.docx
Literatur
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