MCDA swing weighting and discrete choice experiments for elicitation of patient benefit-risk preferences: a critical assessment

Pharmacoepidemiol Drug Saf. 2017 Dec;26(12):1483-1491. doi: 10.1002/pds.4255. Epub 2017 Jul 11.

Abstract

Purpose: Multiple criteria decision analysis swing weighting (SW) and discrete choice experiments (DCE) are appropriate methods for capturing patient preferences on treatment benefit-risk trade-offs. This paper presents a qualitative comparison of the 2 methods.

Methods: We review and critically assess similarities and differences of SW and DCE based on 6 aspects: comprehension by study participants, cognitive biases, sample representativeness, ability to capture heterogeneity in preferences, reliability and validity, and robustness of the results.

Results: The SW choice task can be more difficult, but the workshop context in which SW is conducted may provide more support to patients who are unfamiliar with the end points being evaluated or who have cognitive impairments. Both methods are similarly prone to a number of biases associated with preference elicitation, and DCE is prone to simplifying heuristics, which limits its application with large number of attributes. The low cost per patient of the DCE means that it can be better at achieving a representative sample, though SW does not require such large sample sizes due to exact nature of the collected preference data. This also means that internal validity is automatically enforced with SW, while the internal validity of DCE results needs to be assessed manually.

Conclusions: Choice between the 2 methods depends on characteristics of the benefit-risk assessment, especially on how difficult the trade-offs are for the patients to make and how many patients are available. Although there exist some empirical studies on many of the evaluation aspects, critical evidence gaps remain.

Keywords: benefit-risk assessment; discrete choice experiment; multicriteria decision analysis; pharmacoepidemiology; swing weighting.

MeSH terms

  • Choice Behavior
  • Decision Making*
  • Decision Support Techniques*
  • Humans
  • Patient Preference*
  • Risk Assessment