Mapping the Insomnia Severity Index instrument to EQ-5D health state utilities: a United Kingdom perspective

Chalet, F.-X., Bujaroska, T., Germeni, E. , Ghandri, N., Maddalena, E. T., Modi, K., Olopoenia, A., Thompson, J., Togninalli, M. and Briggs, A. H. (2023) Mapping the Insomnia Severity Index instrument to EQ-5D health state utilities: a United Kingdom perspective. PharmacoEconomics - Open, 7, pp. 149-161. (doi: 10.1007/s41669-023-00388-0) (PMID:36703022) (PMCID:PMC9928998)

Abstract

Objective: This study aimed to map the Insomnia Severity Index (ISI) to the EQ-5D-3L utility values from a UK perspective. Methods: Source data were derived from the 2020 National Health and Wellness Survey (NHWS) for France, Germany, Italy, Spain, the UK and the US. Ordinary least squares regression, generalised linear model (GLM), censored least absolute deviation, and adjusted limited dependent variable mixture model (ALDVMM) were employed to explore the relationship between ISI total summary score and EQ-5D utility while accounting for adjustment covariates derived from the NHWS. Fitting performance was assessed using standard metrics, including mean-squared error (MSE) and coefficient of determination (R2). Results: A total of 17,955 respondent observations were included, with a mean ISI score of 12.12 ± 5.32 and a mean EQ-5D-3L utility (UK tariff) of 0.71 ± 0.23. GLM gamma-log and ALDVMM were the two best performing models. The ALDVMM had better fitting performance (R2 = 0.320, MSE 0.0347) than the GLM gamma-log (R2 = 0.303, MSE 0.0353); in train-test split-sample validation, ALDVMM also slightly outperformed the GLM gamma-log model, with an MSE of 0.0351 versus 0.0355. Based on fitting performance, ALDVMM and GLM gamma-log were the preferred models. Conclusions: In the absence of preference-based measures, this study provides an updated mapping algorithm for estimating EQ-5D-3L utilities from the ISI summary total score. This new mapping not only draws its strengths from the use of a large international dataset but also the incorporation of adjustment variables (including sociodemographic and general health characteristics) to reduce the effects of confounders.

• Item Type: Articles
• Additional Information: Idorsia Pharmaceuticals Ltd funded this research study, including access to the NHWS data and the analytical work by Visium.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Germeni, Dr Evi

Creator Roles

Germeni, E.: Writing – review and editing

• Authors: Chalet, F.-X., Bujaroska, T., Germeni, E., Ghandri, N., Maddalena, E. T., Modi, K., Olopoenia, A., Thompson, J., Togninalli, M., and Briggs, A. H.
• College/School: College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Health Economics and Health Technology Assessment
• Journal Name: PharmacoEconomics - Open
• Publisher: Springer
• ISSN: 2509-4262
• ISSN (Online): 2509-4254
• Published Online: 26 January 2023
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in PharmacoEconomics - Open 7(1):149-161
• Publisher Policy: Reproduced under a Creative Commons License