Article Text
Abstract
Introduction Social value sets (=QALY/DALY-weights) are essential inputs for HTA. To derive a social value set, various methods have been used, including time trade-off, or discrete choice experiments. However, all of these methods suffer from a major limitation: they are inefficient. Little information is obtained from each participant. As a result, data from hundreds if not thousands of participants is required. This limits the ability to derive value sets in resource-constrained settings or for small (patient) groups. Here, we report on the development of the ‘OPUF tool’; a new online survey method for estimating value sets for the EQ-5D-5L (or any other health descriptive system). The approach is more efficient than conventional methods, and even allows estimating value sets on the individual level.
Methods The OPUF approach combines different compositional preference elicitation techniques into a new type of online survey. It broadly consists of three steps: dimension weighting, level rating, and anchoring. We tested the feasibility of using the OPUF survey to derive group-, subgroup-, and individual-level value sets for the EQ-5D-5L in the UK. An interactive demo version of the survey is available at: https://eq5d5l.me.
Results A representative sample (N = 1,000) of the UK population was recruited in August 2021. On average, it took participants about nine minutes to complete the survey. Data from 874 participants were included in the analysis.
We successfully constructed a personal EQ-5D-5L value set for each participant, and aggregate value sets for various subgroups. The validity of the models were assessed against the results from discrete choice experiments: the constructed personal value sets predicted participants’ choices with an accuracy of 78.5%.
Conclusion Although the development of the OPUF tool is in an early stage, we think there are multiple potential applications and avenues for further research (e.g. patient decision-aid).
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ .