Benjamin M Craig1,2. 1. Health Outcomes & Behavior Program, Moffitt Cancer Center, 12902 Magnolia Drive, MRC-CANCONT, Tampa, FL, 33612-9416, USA. benjamin.craig@moffitt.org. 2. Department of Economics, University of South Florida, Tampa, FL, USA. benjamin.craig@moffitt.org.
Abstract
PURPOSE: In the original SF-6D valuation study, the analytical design inherited conventions that detrimentally affected its ability to predict values on a quality-adjusted life year (QALY) scale. Our objective is to estimate UK values for SF-6D states using the original data and multi-attribute utility (MAU) regression after addressing its limitations and to compare the revised SF-6D and EQ-5D value predictions. METHODS: Using the unaltered data (611 respondents, 3503 SG responses), the parameters of the original MAU model were re-estimated under three alternative error specifications, known as the instant, episodic, and angular random utility models. Value predictions on a QALY scale were compared to EQ-5D3L predictions using the 1996 Health Survey for England. RESULTS: Contrary to the original results, the revised SF-6D value predictions range below 0 QALYs (i.e., worse than death) and agree largely with EQ-5D predictions after adjusting for scale. Although a QALY is defined as a year in optimal health, the SF-6D sets a higher standard for optimal health than the EQ-5D-3L; therefore, it has larger units on a QALY scale by construction (20.9 % more). CONCLUSIONS: Much of the debate in health valuation has focused on differences between preference elicitation tasks, sampling, and instruments. After correcting errant econometric practices and adjusting for differences in QALY scale between the EQ-5D and SF-6D values, the revised predictions demonstrate convergent validity, making them more suitable for UK economic evaluations compared to original estimates.
PURPOSE: In the original SF-6D valuation study, the analytical design inherited conventions that detrimentally affected its ability to predict values on a quality-adjusted life year (QALY) scale. Our objective is to estimate UK values for SF-6D states using the original data and multi-attribute utility (MAU) regression after addressing its limitations and to compare the revised SF-6D and EQ-5D value predictions. METHODS: Using the unaltered data (611 respondents, 3503 SG responses), the parameters of the original MAU model were re-estimated under three alternative error specifications, known as the instant, episodic, and angular random utility models. Value predictions on a QALY scale were compared to EQ-5D3L predictions using the 1996 Health Survey for England. RESULTS: Contrary to the original results, the revised SF-6D value predictions range below 0 QALYs (i.e., worse than death) and agree largely with EQ-5D predictions after adjusting for scale. Although a QALY is defined as a year in optimal health, the SF-6D sets a higher standard for optimal health than the EQ-5D-3L; therefore, it has larger units on a QALY scale by construction (20.9 % more). CONCLUSIONS: Much of the debate in health valuation has focused on differences between preference elicitation tasks, sampling, and instruments. After correcting errant econometric practices and adjusting for differences in QALY scale between the EQ-5D and SF-6D values, the revised predictions demonstrate convergent validity, making them more suitable for UK economic evaluations compared to original estimates.
Entities:
Keywords:
EQ-5D; Quality of life; SF-6D; Time trade-off; UK
Authors: Cam Donaldson; Rachel Baker; Helen Mason; Michael Jones-Lee; Emily Lancsar; John Wildman; Ian Bateman; Graham Loomes; Angela Robinson; Robert Sugden; Jose Luis Pinto Prades; Mandy Ryan; Phil Shackley; Richard Smith Journal: BMC Health Serv Res Date: 2011-01-11 Impact factor: 2.655