Discrete choice experiments in pharmacy: a review of the literature

Int J Pharm Pract. 2013 Feb;21(1):3-19. doi: 10.1111/ijpp.12002. Epub 2012 Nov 20.

Abstract

Objective: Discrete choice experiments (DCEs) have been widely used to elicit patient preferences for various healthcare services and interventions. The aim of our study was to conduct an in-depth scoping review of the literature and provide a current overview of the progressive application of DCEs within the field of pharmacy.

Methods: Electronic databases (MEDLINE, EMBASE, SCOPUS, ECONLIT) were searched (January 1990-August 2011) to identify published English language studies using DCEs within the pharmacy context. Data were abstracted with respect to DCE methodology and application to pharmacy.

Key findings: Our search identified 12 studies. The DCE methodology was utilised to elicit preferences for different aspects of pharmacy products, therapy or services. Preferences were elicited from either patients or pharmacists, with just two studies incorporating the views of both. Most reviewed studies examined preferences for process-related or provider-related aspects with a lesser focus on health outcomes. Monetary attributes were considered to be important by most patients and pharmacists in the studies reviewed. Logit, probit or multinomial logit models were most commonly employed for estimation.

Conclusion: Our study showed that the pharmacy profession has adopted the DCE methodology consistent with the general health DCEs although the number of studies is quite limited. Future studies need to examine preferences of both patients and providers for particular products or disease-state management services. Incorporation of health outcome attributes in the design, testing for external validity and the incorporation of DCE results in economic evaluation framework to inform pharmacy policy remain important areas for future research.

Publication types

  • Review

MeSH terms

  • Choice Behavior*
  • Humans
  • Patient Preference / statistics & numerical data*
  • Pharmaceutical Services / statistics & numerical data*
  • Pharmacists / psychology
  • Research Design*