Literature DB >> 30098678

Advocating a Paradigm Shift in Health-State Valuations: The Estimation of Time-Preference Corrected QALY Tariffs.

Marcel F Jonker1, Bas Donkers2, Esther W de Bekker-Grob3, Elly A Stolk4.   

Abstract

BACKGROUND: Despite evidence of nonproportional trade-offs in time trade-off exercises and the explicit incorporation of exponential discounting in health technology assessment calculations, quality-adjusted life-year (QALY) tariffs are currently still established under the assumption of linear time preferences.
OBJECTIVES: The aim of this study was to introduce a general method of accommodating for nonlinear time preferences in discrete choice experiment (DCE) duration studies and to evaluate its impact on estimated QALY tariffs.
METHODS: A parsimonious utility function is proposed that accommodates any discounting function and preserves linear time preferences as a special case. Based on an efficient DCE design and 1775 respondents from a nationally representative scientific household panel, preferences and QALY tariffs for the Dutch SF-6D were estimated while accommodating for nonlinear time preferences via exponential and hyperbolic discounting functions.
RESULTS: When the discount rate was estimated directly, we found strong evidence of nonlinear time preferences (with an exponential and hyperbolic discount rate of 5.7% and 16.5%, respectively). When the discount rate was estimated as a function of health state severity, we found that years lived in better health states are discounted minus years lived in impaired health states. Finally, the best statistical fit was obtained when using a hyperbolic discount function, which resulted in smaller QALY decrements and fewer health states classified as worse than immediate death.
CONCLUSIONS: Our results highlight the relevance and even necessity of a paradigm shift in health valuation studies in favor of time-preference corrected QALY tariffs, with potentially important implications for health technology assessment calculations and regulatory decisions.
Copyright © 2018 ISPOR–The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  QALY; SF-6D; discrete choice experiment; health state valuation

Mesh:

Year:  2018        PMID: 30098678     DOI: 10.1016/j.jval.2018.01.016

Source DB:  PubMed          Journal:  Value Health        ISSN: 1098-3015            Impact factor:   5.725


  6 in total

1.  Does Device or Connection Type Affect Health Preferences in Online Surveys?

Authors:  John D Hartman; Benjamin M Craig
Journal:  Patient       Date:  2019-12       Impact factor: 3.883

2.  Discrete choice experiments to generate utility values for multi-attribute utility instruments: a systematic review of methods.

Authors:  Mina Bahrampour; Joshua Byrnes; Richard Norman; Paul A Scuffham; Martin Downes
Journal:  Eur J Health Econ       Date:  2020-05-04

3.  Not all respondents use a multiplicative utility function in choice experiments for health state valuations, which should be reflected in the elicitation format (or statistical analysis).

Authors:  Marcel F Jonker; Richard Norman
Journal:  Health Econ       Date:  2021-11-28       Impact factor: 2.395

4.  Attribute level overlap (and color coding) can reduce task complexity, improve choice consistency, and decrease the dropout rate in discrete choice experiments.

Authors:  Marcel F Jonker; Bas Donkers; Esther de Bekker-Grob; Elly A Stolk
Journal:  Health Econ       Date:  2018-12-18       Impact factor: 3.046

5.  Severity-Stratified Discrete Choice Experiment Designs for Health State Evaluations.

Authors:  Sesil Lim; Marcel F Jonker; Mark Oppe; Bas Donkers; Elly Stolk
Journal:  Pharmacoeconomics       Date:  2018-11       Impact factor: 4.981

6.  EQ-VT protocol: one-size-fits-all? Challenges and innovative adaptations used in Egypt: a cross-sectional study.

Authors:  Sahar Al Shabasy; Maggie Abbassi; Samar Farid
Journal:  BMJ Open       Date:  2021-12-23       Impact factor: 2.692

  6 in total

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