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Catalogues of EQ-5D-3L Health-Related Quality of Life Scores for 199 Chronic Conditions and Health Risks for Use in the UK and the USA

Author

Listed:
  • Michael Falk Hvidberg

    (Slagelse Hospital
    University of York)

  • Mónica Hernández Alava

    (University of Sheffield)

Abstract

Background Health-related quality of life (HRQoL) measures are essential in economic evaluation, but sometimes primary sources are unavailable, and information from secondary sources is required. Existing HRQoL UK/US catalogues are based on earlier diagnosis classification systems, amongst other issues. A recently published Danish catalogue merged EQ-5D-3L data from national health surveys with national registers containing patient information on ICD-10 diagnoses, healthcare activities and socio-demographics. Aims To provide (1) UK/US EQ-5D-3L-based HRQoL utility population catalogues for 199 chronic conditions on the basis of ICD-10 codes and health risks and (2) regression models controlling for age, sex, comorbidities and health risks to enable predictions in other populations. Methods UK and US EQ-5D-3L value sets were applied to the EQ-5D-3L responses of the Danish dataset and modelled using adjusted limited dependent variable mixture models (ALDVMMs). Results Unadjusted mean utilities, percentiles and adjusted disutilities based on two ALDVMMs with different control variables were provided for both countries. Diseases from groups M, G, and F consistently had the smallest utilities and the largest negative disutilities: fibromyalgia (M797), sclerosis (G35), rheumatism (M790), dorsalgia (M54), cerebral palsy (G80-G83), post-traumatic stress disorder (F431), dementia (F00-2), and depression (F32, etc.). Risk factors, including stress, loneliness, and BMI30+, were also associated with lower HRQoL. Conclusions This study provides comprehensive catalogues of UK/US EQ-5D-3L HRQoL utilities. Results are relevant in cost-effectiveness analysis, for NICE submissions, and for comparing and identifying facets of disease burden.

Suggested Citation

  • Michael Falk Hvidberg & Mónica Hernández Alava, 2023. "Catalogues of EQ-5D-3L Health-Related Quality of Life Scores for 199 Chronic Conditions and Health Risks for Use in the UK and the USA," PharmacoEconomics, Springer, vol. 41(10), pages 1287-1388, October.
    • Handle: RePEc:spr:pharme:v:41:y:2023:i:10:d:10.1007_s40273-023-01285-4
    DOI: 10.1007/s40273-023-01285-4
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    References listed on IDEAS

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    1. Brazier, John & Ratcliffe, Julie & Salomon, Joshua & Tsuchiya, Aki, 2016. "Measuring and Valuing Health Benefits for Economic Evaluation," OUP Catalogue, Oxford University Press, edition 2, number 9780198725923.
    2. Patrick W. Sullivan & Vahram Ghushchyan, 2006. "Preference-Based EQ-5D Index Scores for Chronic Conditions in the United States," Medical Decision Making, , vol. 26(4), pages 410-420, July.
    3. Mónica Hernández Alava & Allan Wailoo & Fred Wolfe & Kaleb Michaud, 2014. "A Comparison of Direct and Indirect Methods for the Estimation of Health Utilities from Clinical Outcomes," Medical Decision Making, , vol. 34(7), pages 919-930, October.
    4. Anirban Basu & Andrea Manca, 2012. "Regression Estimators for Generic Health-Related Quality of Life and Quality-Adjusted Life Years," Medical Decision Making, , vol. 32(1), pages 56-69, January.
    5. Paul Dolan & Claire Gudex & Paul Kind & Alan Williams, 1995. "A social tariff for EuroQol: results from a UK general population survey," Working Papers 138chedp, Centre for Health Economics, University of York.
    6. Monica Hernandez Alava & Allan Wailoo, 2015. "Fitting adjusted limited dependent variable mixture models to EQ-5D," Stata Journal, StataCorp LP, vol. 15(3), pages 737-750, September.
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