Eliciting Exploratory Patient Preference Data: A Case Study in a Rare Disease.

Abstract

Introduction: Qualitative and quantitative methods provide different and complementary insights into patients' preferences for treatment.

Objective: The aim of this study was to use a novel, mixed-methods approach employing qualitative and quantitative approaches to generate preliminary insights into patient preferences for the treatment of a rare disease-generalized myasthenia gravis (gMG).

Methods: We conducted a mixed-methods study to collect exploratory qualitative and quantitative patient preference information and generate informative results within a condensed timeline (about 4 months). Recruitment was facilitated by an international health research firm. Study participants first reviewed a brief document describing six treatment attributes (to facilitate more efficient review of the material during the focus groups) and were then provided a link to complete an online quantitative survey with a single risk threshold task. They then participated in online focus groups, during which they discussed qualitative questions about their experience with gMG treatment and completed up to three quantitative threshold tasks, the first of which repeated the threshold task from the online survey.

Results: The study elicited both quantitative data on 18 participants' risk tolerance and qualitative data on their treatment experience, additional treatment attributes of importance, the reasoning behind their preferences, and the trade-offs they were willing to make. Most participants (n = 15) chose the same hypothetical treatment in the first threshold task in the online survey and the focus groups. Focus group discussions provided insights into participants' choices in the threshold tasks, confirmed that all the attributes were relevant, and helped clarify what was important about the attributes.

Conclusions: Patient preference information can be collected using a variety of approaches, both qualitative and quantitative, tailored to fit the research needs of a study. The novel mixed-methods approach employed in this study efficiently captured patient preference data that were informative for exploratory research, internal decision making, and future research.