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Title: | Impact of mapped EQ-5D utilities on cost-effectiveness analysis: in the case of dialysis treatments | Authors: | Yang, F Devlin, N Luo, N |
Keywords: | Article bootstrapping cost effectiveness analysis cost utility analysis European Quality of Life 5 Dimensions questionnaire human major clinical study Markov chain peritoneal dialysis priority journal quality adjusted life year quality of life reimbursement renal replacement therapy Short Form 12 cost benefit analysis dialysis economics health care cost hemodialysis procedures statistics and numerical data Cost-Benefit Analysis Dialysis Health Care Costs Humans Markov Chains Peritoneal Dialysis Quality-Adjusted Life Years Renal Dialysis |
Issue Date: | 2019 | Citation: | Yang, F, Devlin, N, Luo, N (2019). Impact of mapped EQ-5D utilities on cost-effectiveness analysis: in the case of dialysis treatments. European Journal of Health Economics 20 (1) : 99-105. ScholarBank@NUS Repository. https://doi.org/10.1007/s10198-018-0987-x | Rights: | Attribution 4.0 International | Abstract: | Objectives: This study aimed to evaluate the performance of EQ-5D data mapped from SF-12 in terms of estimating cost effectiveness in cost-utility analysis (CUA). The comparability of SF-6D (derived from SF-12) was also assessed. Methods: Incremental quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs) were calculated based on two Markov models assessing the cost effectiveness of haemodialysis (HD) and peritoneal dialysis (PD) using utility values based on EQ-5D-5L, EQ-5D using three direct-mapping algorithms and two response-mapping algorithms (mEQ-5D), and SF-6D. Bootstrap method was used to estimate the 95% confidence interval (percentile method) of incremental QALYs and ICERs with 1000 replications for the utilities. Results: In both models, compared to the observed EQ-5D values, mEQ-5D values expressed much lower incremental QALYs (range − 14.9 to − 33.2%) and much higher ICERs (range 17.5 to 49.7%). SF-6D also estimated lower incremental QALYs (− 29.0 and − 14.9%) and higher ICERs (40.9 and 17.5%) than did the observed EQ-5D. The 95% confidence interval of incremental QALYs and ICERs confirmed the lower incremental QALYs and higher ICERs estimated using mEQ-5D and SF-6D. Conclusion: Compared to observed EQ-5D, EQ-5D mapped from SF-12 and SF-6D would under-estimate the QALYs gained in cost-utility analysis and thus lead to higher ICERs. It would be more sensible to conduct CUA studies using directly collected EQ-5D data and to designate one single preference-based measure as reference case in a jurisdiction to achieve consistency in healthcare decision-making. © 2018, The Author(s). | Source Title: | European Journal of Health Economics | URI: | https://scholarbank.nus.edu.sg/handle/10635/181162 | ISSN: | 16187598 | DOI: | 10.1007/s10198-018-0987-x | Rights: | Attribution 4.0 International |
Appears in Collections: | Elements Staff Publications |
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