Hence, 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 An extensive search of the literature was conducted to identify published English language studies using

DCEs within the pharmacy context. The following databases were searched between January 1990 and August 2011: MEDLINE, EMBASE, SCOPUS Natural Product Library high throughput and ECONLIT. Search strategies were formulated for individual databases using the following keywords: ‘discrete choice’ or ‘discrete choice experiment’ or ‘discrete choice analysis’ or ‘discrete choice modelling’ or ‘conjoint’ or ‘conjoint analysis’ or ‘stated preference method’ AND ‘pharmacy’ or ‘pharmacies’ or ‘community pharmacy’ or ‘pharmacist’ or ‘pharmacy service’ or ‘pharmaceutical service’ or ‘pharmaceutical care’ or ‘pharmaceutical program’ or ‘specialized service’ or ‘cognitive service’ find more or ‘disease management’ or ‘chemist’. Studies were limited to those that used choice-based techniques, were applicable to pharmacy and were written in English. Reviews, conference

papers, commentaries and letters were excluded. ● Choice-based studies: We limited our analyses to utility-based choice studies including discrete choice experiments and conjoint analysis with a choice-based response format. Studies that presented methodological issues or used conjoint analysis with ranking or rating were not included. ● Applicability to pharmacy: This included choice-based studies that elicited (1) patient preferences for pharmacy-delivered products/services, pharmacies and/or pharmacists; (2) pharmacists preferences for products, treatments, services or job-choices; (3) preferences of both, patients and pharmacists; or (4) informed pharmacy policy or the decision-making framework. Two authors independently reviewed titles and abstracts

and all potential articles meeting the inclusion criteria were downloaded/obtained for additional review. The two authors conducted data abstraction independently and in duplicate and reached consensus through discussion about any disagreement. Included papers were organised and analysed for the following: A DCE is conducted in several stages.[23, 26] Readers are referred to Ryan et al.[26] and Payne and Protirelin Elliot[23] for a description of the different stages. The first step of a DCE is to identify attributes and levels that adequately describe the service or intervention to be evaluated. The next important step of the DCE methodology is the development of the experimental design, hypothetical scenarios and construction of choice sets. The identified attributes and levels are formed into scenarios. The number of possible scenarios that must be included in the experiment to incorporate the total number of combinations of attributes and levels is called a ‘full factorial design’.