Health researchers design discrete-choice experiments (DCEs) to elicit preferences over attributes that define medical treatments. A DCE can accommodate a limited number of attributes, and researchers must decide which attributes to include based on numerous factors. For situations where researchers want information about the possible impact of a treatment attribute not included in the DCE, we propose a method using a fixed follow-up question to the DCE experiment. The follow-up question includes the attributes in the DCE with fixed levels and an additional attribute originally excluded from the DCE. The DCE data can be used to predict the probability that respondents would select one treatment profile over another without the additional attribute. Comparing the prediction to the percentage of the sample who selected each profile when it includes the additional attribute provides information on the potential impact of the additional attribute on choice. We provide an example using data from a DCE study on treatments for chronic lymphocytic leukemia. Cost was excluded from a DCE experiment, but the survey included a follow-up question with two fixed profiles and a cost for each profile. Preferences were sensitive to modest changes in treatment cost, highlighting the importance of gathering this information.
