Mapping of the Insomnia Severity Index and other sleep measures to EuroQol EQ-5D health state utilities

BACKGROUND This study sought to map the Insomnia Severity Index (ISI) and symptom variables onto the EQ-5D. METHODS A cross-sectional survey was conducted among adult US residents with self-reported sleep problems. Respondents provided demographic, comorbidity, and sleep-related information and had completed the ISI and the EQ-5D profile. Respondents were classified into ISI categories indicating no, threshold, moderate, or severe insomnia. Generalized linear models (GLM) were used to map the ISI's 7 items (Model I), summary scores (Model II), clinical categories (Model III), and insomnia symptoms (Model IV), onto the EQ-5D. We used 50% of the sample for estimation and 50% for prediction. Prediction accuracy was assessed by mean squared errors (MSEs) and mean absolute errors (MAEs). RESULTS Mean (standard deviation) sleep duration for respondents (N = 2,842) was 7.8 (1.9) hours, and mean ISI score was 14.1 (4.8). Mean predicted EQ-5D utility was 0.765 (0.08) from Models I-III, which overlapped with observed utilities 0.765 (0.18). Predicted utility using insomnia symptoms was higher (0.771(0.07)). Based on Model I, predicted utilities increased linearly with improving ISI (0.493 if ISI = 28 vs. 1.00 if ISI = 0, p < 0.01). From Model II, each unit decrease in ISI summary score was associated with a 0.022 (p < 0.001) increase in utility. Predicted utilities were 0.868, 0.809, 0.722, and 0.579, respectively, for the 4 clinical categories, suggesting that lower utility was related to greater insomnia severity. The symptom model (Model IV) indicated a concave sleep-duration function of the EQ-5D; thus, utilities diminished after an optimal amount of sleep. The MSEs/MAEs were substantially lower when predicting EQ-5D > 0.40, and results were comparable in all models. CONCLUSIONS Findings suggest that mapping relationships between the EQ-5D and insomnia measures could be established. These relationships may be used to estimate insomnia-related treatment effects on health state utilities.