Mapping between 6 Multiattribute Utility Instruments

Gang Chen · Munir Ahmed Khan · Angelo Iezzi · Julie Ratcliffe · Jeff R. J. Richardson

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Health Systems, Economic Evaluations, Quality of Life Economic and Environmental Valuation Delphi Technique in Research

Abstract

BACKGROUND: Cost-utility analyses commonly employ a multiattribute utility (MAU) instrument to estimate the health state utilities, which are needed to calculate quality-adjusted life years. Different MAU instruments predict significantly different utilities, which makes comparison of results from different evaluation studies problematical. AIM: This article presents mapping functions ("crosswalks") from 6 MAU instruments (EQ-5D-5L, SF-6D, Health Utilities Index 3 [HUI 3], 15D, Quality of Well-Being [QWB], and Assessment of Quality of Life 8D [AQoL-8D]) to each of the other 5 instruments in the study: a total of 30 mapping functions. METHODS: Data were obtained from a multi-instrument comparison survey of the public and patients in 7 disease areas conducted in 6 countries (Australia, Canada, Germany, Norway, United Kingdom, and United States). The 8022 respondents were administered each of the 6 study instruments. Mapping equations between each instrument pair were estimated using 4 econometric techniques: ordinary least squares, generalized linear model, censored least absolute deviations, and, for the first time, a robust MM-estimator. RESULTS: Goodness-of-fit indicators for each of the results are within the range of published studies. Transformations reduced discrepancies between predicted utilities. Incremental utilities, which determine the value of quality-related health benefits, are almost perfectly aligned at the sample means. CONCLUSION: Transformations presented here align the measurement scales of MAU instruments. Their use will increase confidence in the comparability of evaluation studies, which have employed different MAU instruments.

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1996Forming inferences about some intraclass correlation coefficients.2009A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures 2007Comparing the Incomparable? A Systematic Review of Competing Techniques for Converting Descriptive Measures of Health Status into QALY-Weights 2009Toward a Consensus on the QALY 2014Modelling utility weights for the Assessment of Quality of Life (AQoL)-8D 2009Comparison of 5 Health-Related Quality-of-Life Indexes Using Item Response Theory Analysis 2014Multiattribute Utility Instruments and Their Use 2009Predicting EQ-5D utility scores from the 25-item National Eye Institute Vision Function Questionnaire (NEI-VFQ 25) in patients with age-related macular degeneration

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