Comparison of Preference Elicitation Methods Suitable for Small Sample Sizes

Research Contributors: Will King, Valeria M. Toledo-Gallegos, Sarah Hill, Yemi Oluboyede

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ABSTRACT:

Patient preference studies play an increasingly important role in healthcare research, particularly in the development, evaluation, and delivery of interventions for rare diseases and other small-sample contexts. This white paper presents a structured comparison of four stated preference elicitation methods: Discrete Choice Experiment (DCE), Best-Worst Scaling (BWS), Multidimensional Thresholding (MDT) and Online Personal Utility Functions (OPUF). Each method is assessed in terms of its suitability for small-sample applications, considering statistical power, cognitive burden, methodological maturity, design complexity, ease of analysis and ability to explore preference heterogeneity. Drawing on both theoretical frameworks and empirical studies, the paper explores the relative advantages and limitations of each method. It also includes two interactive examples: a DCE and a profile-case BWS survey, which demonstrate the participant experience and provide practical insight into how these methods are implemented. These embedded tools offer a more intuitive and practical understanding of survey design and preference elicitation methods in practice. While DCE and BWS are well-established in health economics research, MDT and OPUF represent promising newer approaches that offer distinct benefits in small-sample contexts. MDT allows for precise, individual-level preference elicitation through structured trade-off tasks, while OPUF offers a simple and efficient compositional method that can be used even with single respondents. The paper concludes that method selection should always be guided by the specific research context, including the characteristics of the target population, resource availability and study goals. Our longstanding expertise in rare disease strategy and patient preference research positions the team to support clients in selecting and implementing these methods effectively. By tailoring study design to the unique needs of each project, we help ensure that preference evidence is both robust and relevant in supporting clinical development and access strategy.

Key Take Home Messages: 

• No single method fits all contexts: The choice of preference elicitation method should be tailored to the study’s objectives, sample size, and target population characteristics.
• Small samples require innovative approaches: Methods like MDT and OPUF are particularly well suited to rare disease and hard-to-reach populations due to their ability to generate reliable individual-level preferences from small samples.
• Established vs. emerging methods: DCE and BWS are widely used and validated, while MDT and OPUF offer innovative alternatives that may be more efficient or less burdensome in specific scenarios.
• Putnam provides expert support: With deep experience in rare disease strategy and preference research, Putnam helps researchers and developers apply the most appropriate and defensible methods across the product lifecycle.

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