Donna Rowen1, Katherine Stevens2, Alexander Labeit2, Jackie Elliott3, Brendan Mulhern4, Jill Carlton2, Hasan Basarir5, Julie Ratcliffe6, John Brazier2. 1. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK. Electronic address: d.rowen@sheffield.ac.uk. 2. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, Sheffield, UK. 3. Academic Unit of Diabetes, Endocrinology and Metabolism, Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK. 4. Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, New South Wales, Australia. 5. Health Economics Unit, University of Birmingham, Birmingham, UK. 6. Institute for Choice, Business School, University of South Australia, Adelaide, Australia.
Abstract
OBJECTIVES: To describe the use of a novel approach in health valuation of a discrete-choice experiment (DCE) including a cost attribute to value a recently developed classification system for measuring the quality-of-life impact (both health and treatment experience) of self-management for diabetes. METHODS: A large online survey was conducted using DCE with cost on UK respondents from the general population (n = 1497) and individuals with diabetes (n = 405). The data were modeled using a conditional logit model with robust standard errors. The marginal rate of substitution was used to generate willingness-to-pay (WTP) estimates for every state defined by the classification system. Robustness of results was assessed by including interaction effects for household income. RESULTS: There were some logical inconsistencies and insignificant coefficients for the milder levels of some attributes. There were some differences in the rank ordering of different attributes for the general population and diabetic patients. The WTP to avoid the most severe state was £1118.53 per month for the general population and £2356.02 per month for the diabetic patient population. The results were largely robust. CONCLUSIONS: Health and self-management can be valued in a single classification system using DCE with cost. The marginal rate of substitution for key attributes can be used to inform cost-benefit analysis of self-management interventions in diabetes using results from clinical studies in which this new classification system has been applied. The method shows promise, but found large WTP estimates exceeding the cost levels used in the survey.
OBJECTIVES: To describe the use of a novel approach in health valuation of a discrete-choice experiment (DCE) including a cost attribute to value a recently developed classification system for measuring the quality-of-life impact (both health and treatment experience) of self-management for diabetes. METHODS: A large online survey was conducted using DCE with cost on UK respondents from the general population (n = 1497) and individuals with diabetes (n = 405). The data were modeled using a conditional logit model with robust standard errors. The marginal rate of substitution was used to generate willingness-to-pay (WTP) estimates for every state defined by the classification system. Robustness of results was assessed by including interaction effects for household income. RESULTS: There were some logical inconsistencies and insignificant coefficients for the milder levels of some attributes. There were some differences in the rank ordering of different attributes for the general population and diabeticpatients. The WTP to avoid the most severe state was £1118.53 per month for the general population and £2356.02 per month for the diabeticpatient population. The results were largely robust. CONCLUSIONS: Health and self-management can be valued in a single classification system using DCE with cost. The marginal rate of substitution for key attributes can be used to inform cost-benefit analysis of self-management interventions in diabetes using results from clinical studies in which this new classification system has been applied. The method shows promise, but found large WTP estimates exceeding the cost levels used in the survey.
Authors: Basil G Bereza; Doug Coyle; Derek Y So; Zbigniew Kadziola; George Wells; Paul Grootendorst; Emmanuel A Papadimitropoulos Journal: Clinicoecon Outcomes Res Date: 2020-03-19
Authors: Anna L Barker; Geeske Peeters; Renata T Morello; Richard Norman; Darshini Ayton; Jeffrey Lefkovits; Angela Brennan; Sue M Evans; John Zalcberg; Christopher Reid; Susannah Ahern; Sze-Ee Soh; Johannes Stoelwinder; John J McNeil Journal: BMJ Open Date: 2018-10-18 Impact factor: 2.692