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      The Danish EQ-5D-5L Value Set: A Hybrid Model Using cTTO and DCE Data

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          Abstract

          Objectives

          Quality-adjusted life-years (QALYs) are expected to be used for priority setting of hospital-dispensed medicines in Denmark from 2021. The aim of this study was to develop the first Danish value set for the EQ-5D-5L based on interviews with a representative sample of the Danish adult population.

          Methods

          A nationally representative sample based on age (> 18 years), gender, education, and geographical region was recruited using data provided by Statistics Denmark. Computer-assisted personal interviews were carried out using the EQ-VT 2.1. Respondents each valued ten health states using composite time trade-off (cTTO) and seven health states using discrete-choice experiment (DCE). Different predictive models were explored using cTTO and DCE data alone or in combination as hybrid models. Model performance was assessed using logical consistency.

          Results

          A total of 1014 interviews were included in the analyses. The sample was representative of the Danish adult population, though the sample contained slightly more respondents with higher education than in the general population. Only the heteroscedastic censored hybrid model combining cTTO and DCE data yielded consistent results, and hence was chosen for modelling the final Danish value set. The predicted values ranged from − 0.757 to 1, and anxiety/depression was the dimension assigned most value by respondents.

          Conclusions

          This study established the Danish EQ-5D-5L value set, which represents the preferences of the Danish general population, and is expected to provide key input for healthcare decision-making in a Danish context.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s40258-021-00639-3.

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          Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L)

          M. Herdman, C. Gudex, S Lloyd … (2011)
          Purpose This article introduces the new 5-level EQ-5D (EQ-5D-5L) health status measure. Methods EQ-5D currently measures health using three levels of severity in five dimensions. A EuroQol Group task force was established to find ways of improving the instrument’s sensitivity and reducing ceiling effects by increasing the number of severity levels. The study was performed in the United Kingdom and Spain. Severity labels for 5 levels in each dimension were identified using response scaling. Focus groups were used to investigate the face and content validity of the new versions, including hypothetical health states generated from those versions. Results Selecting labels at approximately the 25th, 50th, and 75th centiles produced two alternative 5-level versions. Focus group work showed a slight preference for the wording ‘slight-moderate-severe’ problems, with anchors of ‘no problems’ and ‘unable to do’ in the EQ-5D functional dimensions. Similar wording was used in the Pain/Discomfort and Anxiety/Depression dimensions. Hypothetical health states were well understood though participants stressed the need for the internal coherence of health states. Conclusions A 5-level version of the EQ-5D has been developed by the EuroQol Group. Further testing is required to determine whether the new version improves sensitivity and reduces ceiling effects.
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            Interim scoring for the EQ-5D-5L: mapping the EQ-5D-5L to EQ-5D-3L value sets.

            Ben Van Hout, M.F. Janssen, You-Shan Feng … (2012)
            A five-level version of the EuroQol five-dimensional (EQ-5D) descriptive system (EQ-5D-5L) has been developed, but value sets based on preferences directly elicited from representative general population samples are not yet available. The objective of this study was to develop values sets for the EQ-5D-5L by means of a mapping ("crosswalk") approach to the currently available three-level version of the EQ-5D (EQ-5D-3L) values sets. The EQ-5D-3L and EQ-5D-5L descriptive systems were coadministered to respondents with conditions of varying severity to ensure a broad range of levels of health across EQ-5D questionnaire dimensions. We explored four models to generate value sets for the EQ-5D-5L: linear regression, nonparametric statistics, ordered logistic regression, and item-response theory. Criteria for the preferred model included theoretical background, statistical fit, predictive power, and parsimony. A total of 3691 respondents were included. All models had similar fit statistics. Predictive power was slightly better for the nonparametric and ordered logistic regression models. In considering all criteria, the nonparametric model was selected as most suitable for generating values for the EQ-5D-5L. The nonparametric model was preferred for its simplicity while performing similarly to the other models. Being independent of the value set that is used, it can be applied to transform any EQ-5D-3L value set into EQ-5D-5L index values. Strengths of this approach include compatibility with three-level value sets. A limitation of any crosswalk is that the range of index values is restricted to the range of the EQ-5D-3L value sets. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
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              Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: a multi-country study

              M. Janssen, A Simon Pickard, Dominik Golicki … (2012)
              Purpose The aim of this study was to assess the measurement properties of the 5-level classification system of the EQ-5D (5L), in comparison with the 3-level EQ-5D (3L). Methods Participants (n = 3,919) from six countries, including eight patient groups with chronic conditions (cardiovascular disease, respiratory disease, depression, diabetes, liver disease, personality disorders, arthritis, and stroke) and a student cohort, completed the 3L and 5L and, for most participants, also dimension-specific rating scales. The 3L and 5L were compared in terms of feasibility (missing values), redistribution properties, ceiling, discriminatory power, convergent validity, and known-groups validity. Results Missing values were on average 0.8 % for 5L and 1.3 % for 3L. In total, 2.9 % of responses were inconsistent between 5L and 3L. Redistribution from 3L to 5L using EQ dimension-specific rating scales as reference was validated for all 35 3L–5L-level combinations. For 5L, 683 unique health states were observed versus 124 for 3L. The ceiling was reduced from 20.2 % (3L) to 16.0 % (5L). Absolute discriminatory power (Shannon index) improved considerably with 5L (mean 1.87 for 5L versus 1.24 for 3L), and relative discriminatory power (Shannon Evenness index) improved slightly (mean 0.81 for 5L versus 0.78 for 3L). Convergent validity with WHO-5 was demonstrated and improved slightly with 5L. Known-groups validity was confirmed for both 5L and 3L. Conclusions The EQ-5D-5L appears to be a valid extension of the 3-level system which improves upon the measurement properties, reducing the ceiling while improving discriminatory power and establishing convergent and known-groups validity.
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                Author and article information

                Contributors
                Cathrine Elgaard Jensen:
                ORCID: http://orcid.org/0000-0001-7300-254X
                cathelgaard@gmail.com
                Journal
                Journal ID (nlm-ta): Appl Health Econ Health Policy
                Journal ID (iso-abbrev): Appl Health Econ Health Policy
                Title: Applied Health Economics and Health Policy
                Publisher: Springer International Publishing (Cham )
                ISSN (Print): 1175-5652
                ISSN (Electronic): 1179-1896
                Publication date (Electronic): 2 February 2021
                Publication date PMC-release: 2 February 2021
                Publication date (Print): 2021
                Volume: 19
                Issue: 4
                Pages: 579-591
                Affiliations
                [1 ]GRID grid.5117.2, ISNI 0000 0001 0742 471X, Department of Clinical Medicine, Danish Center for Healthcare Improvements, , Aalborg University, ; Aalborg, Denmark
                [2 ]GRID grid.7143.1, ISNI 0000 0004 0512 5013, Department of Clinical Research, , University of Southern Denmark and OPEN - Open Patient data Explorative Network, Odense University Hospital, ; Odense, Denmark
                [3 ]GRID grid.7048.b, ISNI 0000 0001 1956 2722, Department of Economics and Business Economics, , Aarhus University, ; Aarhus, Denmark
                [4 ]GRID grid.10825.3e, ISNI 0000 0001 0728 0170, Department of Management and Economics, , University of Southern Denmark, ; Odense, Denmark
                Author information
                http://orcid.org/0000-0001-7300-254X
                Article
                Publisher ID: 639
                DOI: 10.1007/s40258-021-00639-3
                PMC ID: 8270796
                PubMed ID: 33527304
                SO-VID: a61bd2f2-9ea3-46d3-be0c-47867969e2e3
                Copyright © © The Author(s) 2021
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.

                History
                Date accepted : 7 January 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003035, Aase og Ejnar Danielsens Fond;
                Award ID: 20-000055
                Award Recipient :
                Funded by: The Department of Business and Management at Aalborg University
                Funded by: FundRef http://dx.doi.org/10.13039/501100006419, EuroQol Research Foundation;
                Award ID: 20170400
                Award ID: 20170401
                Award Recipient :
                Funded by: The Danish Health Foundation
                Award ID: 18-B-0187
                Award Recipient :
                Funded by: The North Denmark Region
                Categories
                Subject: Original Research Article
                Custom metadata
                issue-copyright-statement © Springer Nature Switzerland AG 2021

                ScienceOpen disciplines: Economics of health & social care
                Data availability:
                ScienceOpen disciplines: Economics of health & social care

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