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Developing attributes and levels for discrete choice experiments using qualitative methods.

Joanna Coast1, Sue Horrocks

  • 1Health Economics Facility, Health Services Management Centre, University of Birmingham, Birmingham, UK. j.coast@bham.ac.uk

Journal of Health Services Research & Policy
|January 25, 2007
PubMed
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Developing attributes for discrete choice experiments (DCEs) requires rigorous qualitative methods. This study highlights the importance of patient interviews in defining attributes for dermatology services, ensuring relevance and improving DCE design.

Area of Science:

  • Health Services Research
  • Patient-Reported Outcomes
  • Discrete Choice Experiments

Background:

  • The initial stages of discrete choice experiments (DCEs), specifically attribute and level development, often lack methodological rigor.
  • This study addresses the need for robust attribute development in DCEs, particularly for healthcare services.

Purpose of the Study:

  • To present a case study on developing attributes and their levels for a DCE examining patient preferences for accessing dermatology specialist services for non-urgent skin conditions.
  • To illustrate the application of qualitative methods in defining DCE attributes grounded in patient experiences.

Main Methods:

  • Semi-structured interviews were conducted with 19 patients experiencing non-urgent dermatological conditions.
  • A purposive sampling strategy ensured maximum variation among participants.

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  • An iterative approach, with concurrent data collection and analysis, was employed until attribute saturation was achieved.

    • Main Results:

    • Three iterative phases of interviews and analysis were completed.
    • Initial iterations identified 'expertise' and 'waiting time' as key attributes.
    • Subsequent iterations incorporated 'individualized care' and 'convenience', fully elaborating all attributes by the third iteration.

    Conclusions:

    • Qualitative methods are essential for defining meaningful attributes in DCEs.
    • A tension exists between the exploratory nature of qualitative research and the need for concise attributes in quantitative modeling.
    • Enhanced reporting standards for attribute development methodologies in DCEs are necessary to improve study quality and comparability.