The Environmental Protection Agency (EPA) is required by law to assure that the use of pesticides does not cause unreasonable risks to humans or the environment when risks are compared with benefits. Weed scientists conduct hundreds of comparative efficacy tests each year, but the results are often of little use to the Agency in benefit assessments because the tests are unpublished or otherwise unavailable to the Agency, the tests are conducted in a manner unusable for regulatory purposes, or there are inconsistencies between tests conducted year to year or at different sites. Despite the lack of high quality data, the Agency is compelled to make the best regulatory decision possible with the information at hand, and it may appear to some that decisions are based more on policy than science. EPA is looking for experimental methods that will improve the quality of benefits data available to the Agency.

The aim of this paper is to demonstrate the use of conjoint analysis (CA) in health services research. Conjoint analysis is first explained, with emphasis on the history of the technique, followed by an explanation of how to carry out such a study and how the results from such a study can be used. The technique is demonstrated with reference to a study that looks at the benefits of in vitro fertilization. It is shown how CA can be used to estimate the relative importance of attributes, the trade-offs individuals make between these attributes, willingness to pay if cost is included as an attribute, and utility or benefit scores for different ways of providing a service. The paper then considers the potential advantages of CA over other, more commonly used benefit assessment instruments. Finally, there is discussion of the issues raised in the design and analysis of CA studies. It is concluded that these issues must be addressed before the technique becomes an established instrument for technology assessment.