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Using the EQ-5D-5L to investigate quality-of-life impacts of disease-modifying therapy policies for people with multiple sclerosis (MS) in New Zealand

Author

Listed:
  • Suzi Claflin

    (University of Tasmania)

  • Julie A. Campbell

    (University of Tasmania)

  • Richard Norman

    (Curtin University)

  • Deborah F. Mason

    (New Zealand Brain Research Institute)

  • Tomas Kalincik

    (CORe The University of Melbourne
    The Royal Melbourne Hospital)

  • Steve Simpson-Yap

    (University of Tasmania
    The University of Melbourne)

  • Helmut Butzkueven

    (Monash University)

  • William M. Carroll

    (Perron Institute)

  • Andrew J. Palmer

    (University of Tasmania
    The University of Melbourne)

  • C. Leigh Blizzard

    (University of Tasmania)

  • Ingrid van der Mei

    (University of Tasmania)

  • Glen J. Henson

    (University of Tasmania)

  • Bruce V. Taylor

    (University of Tasmania)

Abstract

Background Health state utilities (HSU) are a health-related quality-of-life (HRQoL) input for cost-utility analyses used for resource allocation decisions, including medication reimbursement. New Zealand (NZ) guidelines recommend the EQ-5D instruments; however, the EQ-5D-5L may not sufficiently capture psychosocial health. We evaluated HRQoL among people with multiple sclerosis (MS) in NZ using the EQ-5D-5L and assessed the instrument’s discriminatory sensitivity for a NZ MS cohort. Methods Participants were recruited from the NZ MS Prevalence Study. Participants self-completed a 45-min online survey that included the EQ-5D-5L/EQ-VAS. Disability severity was classified using the Expanded Disability Status Scale (EDSS) to categorise participant disability as mild (EDSS: 0–3.5), moderate (EDSS: 4.0–6.0) and severe (EDSS: 6.5–9.5). Anxiety/depression were also measured using the Hospital Anxiety and Depression Score (HADS). In the absence of an EQ-5D-5L NZ tariff, HSUs were derived using an Australian tariff. We evaluated associations between HSUs and participant characteristics with linear regression models. Results 254 participants entered the study. Mean age was 55.2 years, 79.5% were female. Mean (SD) EQ-5D-5L HSU was 0.58 (0.33). Mean (SD) HSUs for disability categories were: mild 0.80 ± 0.17, moderate 0.57 ± 0.21 and severe 0.14 ± 0.32. Twelve percent reported HSU = 1.0 (i.e., no problems in any domain). Participants who had never used a disease-modifying therapy reported a lower mean HSU. Multivariable modelling found that the HADS anxiety score was not associated with EQ-5D-5L. Conclusions HRQoL for people with MS in NZ was lower than comparable countries, including Australia. We suggest a comparison with other generic tools that may have improved sensitivity to mental health.

Suggested Citation

  • Suzi Claflin & Julie A. Campbell & Richard Norman & Deborah F. Mason & Tomas Kalincik & Steve Simpson-Yap & Helmut Butzkueven & William M. Carroll & Andrew J. Palmer & C. Leigh Blizzard & Ingrid van d, 2023. "Using the EQ-5D-5L to investigate quality-of-life impacts of disease-modifying therapy policies for people with multiple sclerosis (MS) in New Zealand," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 24(6), pages 939-950, August.
  • Handle: RePEc:spr:eujhec:v:24:y:2023:i:6:d:10.1007_s10198-022-01518-x
    DOI: 10.1007/s10198-022-01518-x
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    References listed on IDEAS

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    8. Matthew Kennedy-Martin & Bernhard Slaap & Michael Herdman & Mandy Reenen & Tessa Kennedy-Martin & Wolfgang Greiner & Jan Busschbach & Kristina S. Boye, 2020. "Which multi-attribute utility instruments are recommended for use in cost-utility analysis? A review of national health technology assessment (HTA) guidelines," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(8), pages 1245-1257, November.
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    More about this item

    Keywords

    Multi-attribute utility instrument; Quality of life; Health technology assessment; Cost-utility analysis; Cost-effectiveness analysis;
    All these keywords.

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets

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