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      EuroQol Protocols for Time Trade-Off Valuation of Health Outcomes

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          Abstract

          The time trade-off (TTO) valuation technique is widely used to determine utility values of health outcomes to inform quality-adjusted life-year (QALY) calculations for use in economic evaluation. Protocols for implementing TTO vary in aspects such as the trade-off framework, iteration procedure and its administration model and method, training of respondents and interviewers, and quality control of data collection. The most widely studied and utilized TTO valuation protocols are the Measurement and Valuation of Health (MVH) protocol, the Paris protocol and the EuroQol Valuation Technology (EQ-VT) protocol, all developed by members of the EuroQol Group. The MVH protocol and its successor, the Paris protocol, were developed for valuation of EQ-5D-3L health states. Both protocols were designed for a trained interviewer to elicit preferences from a respondent using the conventional TTO framework with a fixed time horizon of 10 years and an iteration procedure combining bisection and titration. Developed for valuation of EQ-5D-5L health states, the EQ-VT protocol adopted a composite TTO framework and made use of computer technology to facilitate data collection. Training and monitoring of interviewers and respondents is a pivotal component of the EQ-VT protocol. Research is underway aiming to further improve the EuroQol protocols, which form an important basis for the current practice of health technology assessment in many countries.

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          Most cited references38

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          EuroQol: the current state of play.

          R. Brooks (1996)
          The EuroQol Group first met in 1987 to test the feasibility of jointly developing a standardised non-disease-specific instrument for describing and valuing health-related quality of life. From the outset the Group has been multi-country, multi-centre, and multi-disciplinary. The EuroQol instrument is intended to complement other forms of quality of life measures, and it has been purposefully developed to generate a cardinal index of health, thus giving it considerable potential for use in economic evaluation. Considerable effort has been invested by the Group in the development and valuation aspects of health status measurement. Earlier work was reported upon in 1990; this paper is a second 'corporate' effort detailing subsequent developments. The concepts underlying the EuroQol framework are explored with particular reference to the generic nature of the instrument. The valuation task is reviewed and some evidence on the methodological requirements for measurement is presented. A number of special issues of considerable interest and concern to the Group are discussed: the modelling of data, the duration of health states and the problems surrounding the state 'dead'. An outline of some of the applications of the EuroQol instrument is presented and a brief commentary on the Group's ongoing programme of work concludes the paper.
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            US valuation of the EQ-5D health states: development and testing of the D1 valuation model.

            The EQ-5D is a brief, multiattribute, preference-based health status measure. This article describes the development of a statistical model for generating US population-based EQ-5D preference weights. A multistage probability sample was selected from the US adult civilian noninstitutional population. Respondents valued 13 of 243 EQ-5D health states using the time trade-off (TTO) method. Data for 12 states were used in econometric modeling. The TTO valuations were linearly transformed to lie on the interval [-1, 1]. Methods were investigated to account for interaction effects caused by having problems in multiple EQ-5D dimensions. Several alternative model specifications (eg, pooled least squares, random effects) also were considered. A modified split-sample approach was used to evaluate the predictive accuracy of the models. All statistical analyses took into account the clustering and disproportionate selection probabilities inherent in our sampling design. Our D1 model for the EQ-5D included ordinal terms to capture the effect of departures from perfect health as well as interaction effects. A random effects specification of the D1 model yielded a good fit for the observed TTO data, with an overall R of 0.38, a mean absolute error of 0.025, and 7 prediction errors exceeding 0.05 in absolute magnitude. The D1 model best predicts the values for observed health states. The resulting preference weight estimates represent a significant enhancement of the EQ-5D's utility for health status assessment and economic analysis in the US.
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              A program of methodological research to arrive at the new international EQ-5D-5L valuation protocol.

              To describe the research that has been undertaken by the EuroQol Group to improve current methods for health state valuation, to summarize the results of an extensive international pilot program, and to outline the key elements of the five-level EuroQol five-dimensional (EQ-5D-5L) questionnaire valuation protocol, which is the culmination of that work.
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                Author and article information

                Contributors
                oppe@euroqol.org
                kim.rand-hendriksen@medisin.uio.no
                KShah@ohe.org
                jramos@euroqol.org
                +65 6516 4966 , nan_luo@nuhs.edu.sg
                Journal
                Pharmacoeconomics
                Pharmacoeconomics
                Pharmacoeconomics
                Springer International Publishing (Cham )
                1170-7690
                1179-2027
                15 April 2016
                15 April 2016
                2016
                : 34
                : 10
                : 993-1004
                Affiliations
                [1 ]EuroQol Research Foundation, Rotterdam, The Netherlands
                [2 ]Health Services Research Centre, Akershus University Hospital, Lørenskog, Norway
                [3 ]Dept. of Health Management and Health Economics, University of Oslo, Oslo, Norway
                [4 ]Office of Health Economics, London, UK
                [5 ]Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive 2, Block MD1, #11-01D, Singapore, 117549 Singapore
                Article
                404
                10.1007/s40273-016-0404-1
                5023738
                27084198
                9dc1965f-c1aa-4bed-8f3e-f7391a6a9de2
                © The Author(s) 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                Funding
                Funded by: The EuroQol Research Foundation
                Award ID: 2015410
                Award Recipient :
                Categories
                Practical Application
                Custom metadata
                © Springer International Publishing Switzerland 2016

                Economics of health & social care
                Economics of health & social care

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