Mapping the Insomnia Severity Index Instrument to EQ-5D Health State Utilities: A United Kingdom Perspective

François-Xavier Chalet (), Teodora Bujaroska, Evi Germeni, Nizar Ghandri, Emilio T. Maddalena, Kushal Modi, Abisola Olopoenia, Jeffrey Thompson, Matteo Togninalli and Andrew H. Briggs
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François-Xavier Chalet: Idorsia Pharmaceuticals Ltd
Teodora Bujaroska: Rte Cantonale
Evi Germeni: University of Glasgow
Nizar Ghandri: Rte Cantonale
Emilio T. Maddalena: Rte Cantonale
Kushal Modi: Cerner Enviza
Abisola Olopoenia: Cerner Enviza
Jeffrey Thompson: Cerner Enviza
Matteo Togninalli: Rte Cantonale
Andrew H. Briggs: London School of Hygiene and Tropical Medicine

PharmacoEconomics - Open, 2023, vol. 7, issue 1, No 13, 149-161

Abstract: 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.

Date: 2023
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DOI: 10.1007/s41669-023-00388-0

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