Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/115539
Citations
Scopus Web of Science® Altmetric
?
?
Type: Journal article
Title: Mapping between 6 multiattribute utility instruments
Author: Chen, G.
Khan, M.
Iezzi, A.
Ratcliffe, J.
Richardson, J.
Citation: Medical Decision Making, 2016; 36(2):160-175
Publisher: SAGE Publications
Issue Date: 2016
ISSN: 0272-989X
1552-681X
Statement of
Responsibility: 
Gang Chen, Munir A. Khan, Angelo Iezzi, Julie Ratcliffe, Jeff Richardson
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.
Keywords: Cost-utility analysis; cost effectiveness analysis; health-related quality of life; utility; mapping
Rights: © The Author(s) 2015
RMID: 0030098648
DOI: 10.1177/0272989X15578127
Grant ID: http://purl.org/au-research/grants/nhmrc/1006334
Appears in Collections:Public Health publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.