Literature DB >> 18556637

Health utility bias: a systematic review and meta-analytic evaluation.

Jason N Doctor1, Han Bleichrodt, H Jill Lin.   

Abstract

BACKGROUND: A common assertion is that rating scale (RS) values are lower than both standard gamble (SG) and time tradeoff (TTO) values. However, differences among these methods may be due to method specific bias. Although SG and TTOs suffer systematic bias, RS responses are known to depend on the range and frequency of other health states being evaluated. Over many diverse studies this effect is predicted to diminish. Thus, a systematic review and data synthesis of RS-TTO and RS-SG difference scores may better reveal persistent dissimilarities.
PURPOSE: The purpose of this study was to establish through systematic review and meta-analysis the net effect of biases that endure over many studies of utilities.
METHODS: A total of 2206 RS and TTO and 1318 RS and SG respondents in 27 studies of utilities participated. MEDLINE was searched for data from 1976 to 2004, complemented by a hand search of full-length articles and conference abstracts for 9 journals known to publish utility studies, as well as review of results and additional recommendations by 5 outside experts in the field. Two investigators abstracted the articles. We contacted the investigators of the original if required information was not available.
RESULTS: No significant effect for RS and TTO difference scores was observed: effect size (95% confidence interval [CI]) = 0.04 (-0.02, 0.09). In contrast, RS scores were significantly lower than SG scores: effect size (95% CI ) =-0.23 (-0.28, -0.19). Correcting SG scores for 3 known biases (loss aversion, framing, and probability weighting) eliminated differences between RS and SG scores: effect size (95% CI ) = 0.01 (-0.03, 0.05). Systematic bias in the RS method may exist but be heretofore unknown. Bias correction formulas were applied to mean not individual utilities.
CONCLUSIONS: The results of this study do not support the common view that RS values are lower than TTO values, may suggest that TTO biases largely cancel, and support the validity of formulas for correcting SG bias.

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Mesh:

Year:  2008        PMID: 18556637     DOI: 10.1177/0272989X07312478

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  17 in total

1.  Valuation of depression co-occurring with a somatic condition: feasibility of the time trade-off task.

Authors:  Katerina Papageorgiou; Karin M Vermeulen; Fenna R M Leijten; Erik Buskens; Adelita V Ranchor; Maya J Schroevers
Journal:  Health Expect       Date:  2014-11-13       Impact factor: 3.377

2.  Validity of standard gamble utilities in patients referred for aortic valve replacement.

Authors:  Amjad I Hussain; Andrew M Garratt; Jan Otto Beitnes; Lars Gullestad; Kjell I Pettersen
Journal:  Qual Life Res       Date:  2015-11-24       Impact factor: 4.147

3.  Differences in the Selection of Health State Utility Values by Sponsorship in Published Cost-Effectiveness Analyses.

Authors:  Nathaniel Hendrix; David D Kim; Krishna S Patel; Beth Devine
Journal:  Med Decis Making       Date:  2021-01-15       Impact factor: 2.583

4.  Validation of the underlying assumptions of the quality-adjusted life-years outcome: results from the ECHOUTCOME European project.

Authors:  Ariel Beresniak; Antonieta Medina-Lara; Jean Paul Auray; Alain De Wever; Jean-Claude Praet; Rosanna Tarricone; Aleksandra Torbica; Danielle Dupont; Michel Lamure; Gerard Duru
Journal:  Pharmacoeconomics       Date:  2015-01       Impact factor: 4.981

5.  What should we know about the person behind a TTO?

Authors:  Floortje van Nooten; Jan Busschbach; Michel van Agthoven; Job van Exel; Werner Brouwer
Journal:  Eur J Health Econ       Date:  2018-12

6.  Quality-adjusted life years lost to road crash injury: updating the injury impairment index.

Authors:  Rebecca S Spicer; Ted R Miller; Delia Hendrie; Lawrence J Blincoe
Journal:  Ann Adv Automot Med       Date:  2011

7.  Predictors of health-related quality-of-life utilities among persons with posttraumatic stress disorder.

Authors:  Jason N Doctor; Lori A Zoellner; Norah C Feeny
Journal:  Psychiatr Serv       Date:  2011-03       Impact factor: 3.084

Review 8.  Valuation of health states in the US study to establish disability weights: lessons from the literature.

Authors:  Jürgen Rehm; Ulrich Frick
Journal:  Int J Methods Psychiatr Res       Date:  2010-03       Impact factor: 4.035

9.  Reference bias: presentation of extreme health states prior to EQ-VAS improves health-related quality of life scores. a randomised cross-over trial.

Authors:  Steven McPhail; Elaine Beller; Terry Haines
Journal:  Health Qual Life Outcomes       Date:  2010-12-02       Impact factor: 3.186

10.  Are patients' judgments of health status really different from the general population?

Authors:  Paul Fm Krabbe; Noor Tromp; Theo Jm Ruers; Piet Lcm van Riel
Journal:  Health Qual Life Outcomes       Date:  2011-05-11       Impact factor: 3.186

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