AI Article Synopsis
- Choice-based conjoint (CBC) helps researchers understand how individuals form preferences based on different attributes of decision alternatives.
- Though widely used in fields like psychology and marketing, CBC is increasingly being applied in healthcare to analyze patient choices regarding policy, drugs, and doctor interactions.
- There is a need for standardized methodologies in applying CBC in healthcare, and the review focuses on recent innovations that improve its effectiveness, including Pareto optimality, enhanced information per profile, and smaller choice sets.
Article Abstract
Choice-based conjoint (CBC) is used to understand how individuals develop preferences for decision alternatives. When decision alternatives can be described in terms of attributes, researchers want to determine the value respondents attach to various attribute levels. Popular in psychology, marketing, economics and other areas, CBC is now finding applications in healthcare to understand patient choice in healthcare policy, drug development, doctor-patient communications, etc. However, a lack of standard methodologies has served as a barrier to its use in healthcare. Therefore, there is a need to identify good research practices for CBC in healthcare. We review recent advances in CBC such as Pareto optimal choice sets, information per profile and reducing choice set sizes, as applied to patient choice.
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| http://dx.doi.org/10.2217/cer-2019-0115 | DOI Listing |
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