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Measuring the Sensitivity and Construct Validity of 6 Utility Instruments in 7 Disease Areas

Author

Listed:
  • Jeff Richardson
  • Angelo Iezzi
  • Munir A. Khan
  • Gang Chen
  • Aimee Maxwell

Abstract

Background. Health services that affect quality of life (QoL) are increasingly evaluated using cost utility analyses (CUA). These commonly employ one of a small number of multiattribute utility instruments (MAUI) to assess the effects of the health service on utility. However, the MAUI differ significantly, and the choice of instrument may alter the outcome of an evaluation. Aims. The present article has 2 objectives: 1) to compare the results of 3 measures of the sensitivity of 6 MAUI and the results of 6 tests of construct validity in 7 disease areas and 2) to rank the MAUI by each of the test results in each disease area and by an overall composite index constructed from the tests. Methods. Patients and the general public were administered a battery of instruments, which included the 6 MAUI, disease-specific QoL instruments (DSI), and 6 other comparator instruments. In each disease area, instrument sensitivity was measured 3 ways: by the unadjusted mean difference in utility between public and patient groups, by the value of the effect size, and by the correlation between MAUI and DSI scores. Content and convergent validity were tested by comparison of MAUI utilities and scores from the 6 comparator instruments. These included 2 measures of health state preferences, measures of subjective well-being and capabilities, and generic measures of physical and mental QoL derived from the SF-36. Results. The apparent sensitivity of instruments varied significantly with the measurement method and by disease area. Validation test results varied with the comparator instruments. Notwithstanding this variability, the 15D, AQoL-8D, and the SF-6D generally achieved better test results than the QWB and EQ-5D-5L.

Suggested Citation

  • Jeff Richardson & Angelo Iezzi & Munir A. Khan & Gang Chen & Aimee Maxwell, 2016. "Measuring the Sensitivity and Construct Validity of 6 Utility Instruments in 7 Disease Areas," Medical Decision Making, , vol. 36(2), pages 147-159, February.
    • Handle: RePEc:sae:medema:v:36:y:2016:i:2:p:147-159
    DOI: 10.1177/0272989X15613522
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    References listed on IDEAS

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    1. Helliwell, John & Layard, Richard & Sachs, Jeffrey, 2012. "World happiness report," LSE Research Online Documents on Economics 47487, London School of Economics and Political Science, LSE Library.
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    1. Micha J. Pilz & Simone Seyringer & Imad Al-Naesan & Madeleine T. King & Andrew Bottomley & Richard Norman & Lisa Schlosser & Tobias Hell & Eva Maria Gamper, 2024. "Cancer-Specific Health Utilities: Evaluation of Core Measurement Properties of the EORTC QLU-C10D in Lung Cancer Patients—Data from Four Multicentre LUX-Lung Trials, Applying Six Country Tariffs," PharmacoEconomics - Open, Springer, vol. 8(4), pages 627-640, July.
    2. Shitong Xie & Jing Wu & Gang Chen, 2024. "Comparative performance and mapping algorithms between EQ-5D-5L and SF-6Dv2 among the Chinese general population," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 25(1), pages 7-19, February.
    3. Andrew J. Palmer & Julie A. Campbell & Barbara de Graaff & Nancy Devlin & Hasnat Ahmad & Philip M Clarke & Mingsheng Chen & Lei Si, 2021. "Population norms for quality adjusted life years for the United States of America, China, the United Kingdom and Australia," Health Economics, John Wiley & Sons, Ltd., vol. 30(8), pages 1950-1977, August.
    4. Gang Chen & Julie Ratcliffe & Billingsley Kaambwa & Nikki McCaffrey & Jeff Richardson, 2018. "Empirical Comparison Between Capability and Two Health-Related Quality of Life Measures," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 140(1), pages 175-190, November.
    5. Paul Mark Mitchell & Samantha Husbands & Sarah Byford & Philip Kinghorn & Cara Bailey & Tim J. Peters & Joanna Coast, 2021. "Challenges in developing capability measures for children and young people for use in the economic evaluation of health and care interventions," Health Economics, John Wiley & Sons, Ltd., vol. 30(9), pages 1990-2003, September.
    6. Myles-Jay Linton & Paul Mark Mitchell & Hareth Al-Janabi & Michael Schlander & Jeff Richardson & Angelo Iezzi & Jasper Ubels & Joanna Coast, 2020. "Comparing the German Translation of the ICECAP-A Capability Wellbeing Measure to the Original English Version: Psychometric Properties across Healthy Samples and Seven Health Condition Groups," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 15(3), pages 651-673, July.
    7. Micha J. Pilz & Simon Seyringer & Lára R. Hallsson & Andrew Bottomley & Femke Jansen & Madeleine T. King & Richard Norman & Marianne J. Rutten & Irma M. Verdonck-de Leeuw & Peter D. Siersema & Eva Mar, 2024. "The EORTC QLU-C10D is a valid cancer-specific preference-based measure for cost-utility and health technology assessment in the Netherlands," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 25(9), pages 1539-1555, December.

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