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https://doi.org/10.1007/s10198-018-0987-x
DC Field | Value | |
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dc.title | Impact of mapped EQ-5D utilities on cost-effectiveness analysis: in the case of dialysis treatments | |
dc.contributor.author | Yang, F | |
dc.contributor.author | Devlin, N | |
dc.contributor.author | Luo, N | |
dc.date.accessioned | 2020-10-27T10:02:52Z | |
dc.date.available | 2020-10-27T10:02:52Z | |
dc.date.issued | 2019 | |
dc.identifier.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 | |
dc.identifier.issn | 16187598 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/181162 | |
dc.description.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). | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.source | Unpaywall 20201031 | |
dc.subject | Article | |
dc.subject | bootstrapping | |
dc.subject | cost effectiveness analysis | |
dc.subject | cost utility analysis | |
dc.subject | European Quality of Life 5 Dimensions questionnaire | |
dc.subject | human | |
dc.subject | major clinical study | |
dc.subject | Markov chain | |
dc.subject | peritoneal dialysis | |
dc.subject | priority journal | |
dc.subject | quality adjusted life year | |
dc.subject | quality of life | |
dc.subject | reimbursement | |
dc.subject | renal replacement therapy | |
dc.subject | Short Form 12 | |
dc.subject | cost benefit analysis | |
dc.subject | dialysis | |
dc.subject | economics | |
dc.subject | health care cost | |
dc.subject | hemodialysis | |
dc.subject | procedures | |
dc.subject | statistics and numerical data | |
dc.subject | Cost-Benefit Analysis | |
dc.subject | Dialysis | |
dc.subject | Health Care Costs | |
dc.subject | Humans | |
dc.subject | Markov Chains | |
dc.subject | Peritoneal Dialysis | |
dc.subject | Quality-Adjusted Life Years | |
dc.subject | Renal Dialysis | |
dc.type | Article | |
dc.contributor.department | SAW SWEE HOCK SCHOOL OF PUBLIC HEALTH | |
dc.description.doi | 10.1007/s10198-018-0987-x | |
dc.description.sourcetitle | European Journal of Health Economics | |
dc.description.volume | 20 | |
dc.description.issue | 1 | |
dc.description.page | 99-105 | |
Appears in Collections: | Elements Staff Publications |
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