OBJECTIVES: Increasingly, conjoint analysis , a stated-preference method, is applied in health outcomes research. Variation in method type and quality make it difficult to assess substantive findings. The ISPOR Conjoint Analysis Database Project was established to identify and evaluate empirical conjoint analysis applications in the literature using the 10-point ISPOR Checklist for Good Research Practice in Conjoint Analysis (the Checklist). METHODS: Multiple electronic databases published between 1980 and 2008 were searched to identify conjoint-analysis applications in human health studies. Only English-language publications were incorporated. Included studies were subject to detailed data extraction including descriptive information, methodological details on survey type, experimental design, survey format, attributes and levels, sample size, number of conjoint tasks per respondent, and analysis methods. Review articles and methods studies were excluded. The detailed extraction form was piloted to identify key elements to be included in the database using a standardized taxonomy and to test the Checklist as an evaluative framework for the methodological assessment of these studies. RESULTS: The search identified 2,365 citations - 264 met inclusion criteria. The number of applied studies increased substantially over time (1980-85 =5 and 2007=42) in a broad range of applications, cancer being the most frequent. Based on the pilot results, discrete-choice experiments using fractional factorial designs were most common. Attribute number ranged from 3-6, choice tasks per respondent ranged from 8-16 and sample size ranged from 30-335. Studies generally reported less information than required by the 10-point Checklist, especially regarding methods used to generate experimental design and reporting design properties. CONCLUSION: Conjoint analysis in health has expanded to include a broad range of applications and methodological approaches. The Checklist provides a framework to assess their quality. The conjoint analysis Database project will complete the assessment of the quality and variability of these studies based on the pilot findings.