Richard Norman1, Rosalie Viney1, John Brazier2, Leonie Burgess3, Paula Cronin1, Madeleine King4, Julie Ratcliffe5, Deborah Street3. 1. Centre for Health Economics Research and Evaluation, University of Technology, Sydney, Australia (RN, RV, PC) 2. School of Health and Related Research, University of Sheffield, UK (JB) 3. Department of Mathematical Sciences, University of Technology, Sydney, Australia (LB, DS) 4. Psycho-oncology Co-operative Research Group, University of Sydney, Australia (MK) 5. Flinders Health Economics Group, Flinders Clinical Effectiveness, Flinders University, Adelaide, Australia (JR).
Abstract
BACKGROUND: SF-6D utility weights are conventionally produced using a standard gamble (SG). SG-derived weights consistently demonstrate a floor effect not observed with other elicitation techniques. Recent advances in discrete choice methods have allowed estimation of utility weights. The objective was to produce Australian utility weights for the SF-6D and to explore the application of discrete choice experiment (DCE) methods in this context. We hypothesized that weights derived using this method would reflect the largely monotonic construction of the SF-6D. METHODS: We designed an online DCE and administered it to an Australia-representative online panel (n = 1017). A range of specifications investigating nonlinear preferences with respect to additional life expectancy were estimated using a random-effects probit model. The preferred model was then used to estimate a preference index such that full health and death were valued at 1 and 0, respectively, to provide an algorithm for Australian cost-utility analyses. RESULTS: Physical functioning, pain, mental health, and vitality were the largest drivers of utility weights. Combining levels to remove illogical orderings did not lead to a poorer model fit. Relative to international SG-derived weights, the range of utility weights was larger with 5% of health states valued below zero. CONCLUSION: s. DCEs can be used to investigate preferences for health profiles and to estimate utility weights for multi-attribute utility instruments. Australian cost-utility analyses can now use domestic SF-6D weights. The comparability of DCE results to those using other elicitation methods for estimating utility weights for quality-adjusted life-year calculations should be further investigated.
BACKGROUND: SF-6D utility weights are conventionally produced using a standard gamble (SG). SG-derived weights consistently demonstrate a floor effect not observed with other elicitation techniques. Recent advances in discrete choice methods have allowed estimation of utility weights. The objective was to produce Australian utility weights for the SF-6D and to explore the application of discrete choice experiment (DCE) methods in this context. We hypothesized that weights derived using this method would reflect the largely monotonic construction of the SF-6D. METHODS: We designed an online DCE and administered it to an Australia-representative online panel (n = 1017). A range of specifications investigating nonlinear preferences with respect to additional life expectancy were estimated using a random-effects probit model. The preferred model was then used to estimate a preference index such that full health and death were valued at 1 and 0, respectively, to provide an algorithm for Australian cost-utility analyses. RESULTS: Physical functioning, pain, mental health, and vitality were the largest drivers of utility weights. Combining levels to remove illogical orderings did not lead to a poorer model fit. Relative to international SG-derived weights, the range of utility weights was larger with 5% of health states valued below zero. CONCLUSION: s. DCEs can be used to investigate preferences for health profiles and to estimate utility weights for multi-attribute utility instruments. Australian cost-utility analyses can now use domestic SF-6D weights. The comparability of DCE results to those using other elicitation methods for estimating utility weights for quality-adjusted life-year calculations should be further investigated.
Authors: Melanie L R Wyld; Rachael L Morton; Phil Clayton; Muh Geot Wong; Meg Jardine; Kevan Polkinghorne; Steve Chadban Journal: Qual Life Res Date: 2019-04-01 Impact factor: 4.147
Authors: M T King; D S J Costa; N K Aaronson; J E Brazier; D F Cella; P M Fayers; P Grimison; M Janda; G Kemmler; R Norman; A S Pickard; D Rowen; G Velikova; T A Young; R Viney Journal: Qual Life Res Date: 2016-01-20 Impact factor: 4.147