Abstract

Introduction Standard valuation methods, such as TTO and DCE are inefficient. They require data from hundreds if not thousands of participants to generate value sets. Here, we present the Online elicitation of Personal Utility Functions (OPUF) tool; a new type of online survey for valuing EQ-5D-5L health states using more efficient, compositional elicitation methods, which even allow estimating value sets on the individual level. The aims of this study are to report on the development of the tool, and to test the feasibility of using it to obtain individual-level value sets for the EQ-5D-5L. Methods We applied an iterative design approach toadapt the PUF method, previously developed by Devlin et al., for use as a standalone online tool. Five rounds of qualitative interviews, and one quantitative pre-pilot were conducted to get feedback on the different tasks. After each round, the tool was refined and re-evaluated. The final version was piloted in a sample of 50 participants from the UK. A demo of the EQ-5D-5L OPUF survey is available at: https://eq5d5l.me Results On average, it took participants about seven minutes to complete the OPUF Tool. Based on the responses, we were able to construct a personal EQ-5D-5L value set for each of the 50 participants. These value sets predicted a participants' choices in a discrete choice experiment with an accuracy of 80%. Overall, the results revealed that health state preferences vary considerably on the individual-level. Nevertheless, we were able to estimate a group-level value set for all 50 participants with reasonable precision. Discussion We successfully piloted the OPUF Tool and showed that it can be used to derive a group-level as well as personal value sets for the EQ-5D-5L. Although the development of the online tool is stillin an early stage, there are multiplepotentialavenues forfurtherresearch.

Highlights

  • Standard valuation methods, such as time trade-off (TTO) and discrete choice experiments (DCE) are inefficient

  • The results revealed that health state preferences vary considerably on the individual-level

  • We were able to estimate a group-level value set for all 50 participants with reasonable precision

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Summary

Introduction

Standard valuation methods, such as TTO and DCE are inefficient They require data from hundreds if not thousands of participants to generate value sets. The QALY is generally derived from generic measures of health, which, in turn, consist of two components: firstly, a health descriptive system, which defines a number of mutually exclusive health states and, secondly, a set of (social) values, that reflect their respective desirability. These values are commonly based on individual preferences of members of the general public[1,2]

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