Abstract

Background

To construct an EQ-5D-5L value set, the EuroQol Group developed a standard protocol named EuroQol Valuation Technology (EQ-VT), prescribing the valuation of 86 health states utilizing the composite time trade-off (cTTO) approach, and subsequently modeled the observed values to yield values for all 3125 states.

Objective

A recent study demonstrated that a 25-state orthogonal design could provide as accurate predictions as the EQ-VT design applying visual analogue scale data. We aimed to test that design using time trade-off (TTO) data.

Method

We collected TTO values utilizing EQ-VT, orthogonal, and D-efficient designs. The EQ-VT design included 86 health states distributed over 3 blocks of 30 states with some duplicates. The orthogonal and D-efficient designs each comprised 1 block of 30 states. A total of 525 university students were asked to value a random block of health states using EQ-PVT (a PowerPoint replica of EQ-VT software), which generated 100 observations per health state in all 3 designs. We modeled data by design and compared the root mean square error (RMSE) between observed and predicted values within and across the designs.

Results

The EQ-VT design had the lowest RMSE of 0.052; the RMSEs for the orthogonal and the D-efficient designs were 0.066 and 0.063, respectively. RMSE results between designs differed for more severe health states. Some coefficients differed between designs.

Conclusion

Smaller designs did not lead to significant increases in prediction errors when modeling TTO data (measuring 0.01 on a utility scale). Resource-constrained countries may use small designs for valuation studies, especially when other types of preference data, such as those from discrete choice experiments, are collected and modeled jointly.