Yan Meng1,2,3, Philip M Clarke1,4, Ilias Goranitis5,6,7. 1. Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, 207-221 Bouverie St., Parkville, Melbourne, VIC, 3010, Australia. 2. Australian Genomics Health Alliance, Melbourne, VIC, Australia. 3. Murdoch Children's Research Institute, Melbourne, VIC, Australia. 4. Nuffield Department of Population Health, Health Economics Research Centre, University of Oxford, Headington, UK. 5. Health Economics Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, 207-221 Bouverie St., Parkville, Melbourne, VIC, 3010, Australia. ilias.goranitis@unimelb.edu.au. 6. Australian Genomics Health Alliance, Melbourne, VIC, Australia. ilias.goranitis@unimelb.edu.au. 7. Murdoch Children's Research Institute, Melbourne, VIC, Australia. ilias.goranitis@unimelb.edu.au.
Abstract
OBJECTIVES: The aim of this study was to elicit the willingness-to-pay (WTP) for genomic testing, using contingent valuation, among people with lived experience of genetic conditions in Australia. METHODS: Parents of children with suspected mitochondrial disorders, epileptic encephalopathy, leukodystrophy, or malformations of cortical development completed a dynamic triple-bounded dichotomous choice (DC) contingent valuation. Adult patients or parents of children with suspected genetic kidney disease or complex neurological and neurodegenerative conditions completed a payment card (PC) contingent valuation. DC data were analyzed using a multilevel interval regression and a multilevel probit model. PC data were analyzed using a Heckman selection model. RESULTS: In total, 360 individuals participated in the contingent valuation (CV), with 141 (39%) and 219 (61%) completing the DC and PC questions, respectively. The mean WTP for genomic testing was estimated at AU$2830 (95% confidence interval [CI] 2236-3424) based on the DC data and AU$1914 (95% CI 1532-2296) based on the PC data. The mean WTP across the six cohorts ranged from AU$1879 (genetic kidney disease) to AU$4554 (leukodystrophy). CONCLUSIONS: Genomic testing is highly valued by people experiencing rare genetic conditions. Our findings can inform cost-benefit analyses and the prioritization of genomics into mainstream clinical care. While our WTP estimates for adult-onset genetic conditions aligned with estimates derived from discrete choice experiments (DCEs), for childhood-onset conditions our estimates were significantly lower. Research is urgently required to directly compare, and critically evaluate, the performance of CV and DCE methods.
OBJECTIVES: The aim of this study was to elicit the willingness-to-pay (WTP) for genomic testing, using contingent valuation, among people with lived experience of genetic conditions in Australia. METHODS: Parents of children with suspected mitochondrial disorders, epileptic encephalopathy, leukodystrophy, or malformations of cortical development completed a dynamic triple-bounded dichotomous choice (DC) contingent valuation. Adult patients or parents of children with suspected genetic kidney disease or complex neurological and neurodegenerative conditions completed a payment card (PC) contingent valuation. DC data were analyzed using a multilevel interval regression and a multilevel probit model. PC data were analyzed using a Heckman selection model. RESULTS: In total, 360 individuals participated in the contingent valuation (CV), with 141 (39%) and 219 (61%) completing the DC and PC questions, respectively. The mean WTP for genomic testing was estimated at AU$2830 (95% confidence interval [CI] 2236-3424) based on the DC data and AU$1914 (95% CI 1532-2296) based on the PC data. The mean WTP across the six cohorts ranged from AU$1879 (genetic kidney disease) to AU$4554 (leukodystrophy). CONCLUSIONS: Genomic testing is highly valued by people experiencing rare genetic conditions. Our findings can inform cost-benefit analyses and the prioritization of genomics into mainstream clinical care. While our WTP estimates for adult-onset genetic conditions aligned with estimates derived from discrete choice experiments (DCEs), for childhood-onset conditions our estimates were significantly lower. Research is urgently required to directly compare, and critically evaluate, the performance of CV and DCE methods.
Authors: You Wu; Hareth Al-Janabi; Andrew Mallett; Catherine Quinlan; Ingrid E Scheffer; Katherine B Howell; John Christodoulou; Richard J Leventer; Paul J Lockhart; Zornitza Stark; Tiffany Boughtwood; Ilias Goranitis Journal: Qual Life Res Date: 2020-04-07 Impact factor: 4.147
Authors: Dean A Regier; Deirdre Weymann; James Buchanan; Deborah A Marshall; Sarah Wordsworth Journal: Value Health Date: 2018-08-18 Impact factor: 5.725
Authors: Michelle M Clark; Zornitza Stark; Lauge Farnaes; Tiong Y Tan; Susan M White; David Dimmock; Stephen F Kingsmore Journal: NPJ Genom Med Date: 2018-07-09 Impact factor: 8.617