US Population Norms for the EQ-5D-5L and Comparison of Norms from Face-to-face and Online Samples

Overview

Journal Qual Life Res

Specialties Pharmacology
Rehabilitation Medicine

Date 2020 Oct 7

PMID 33025373

Citations 76

Authors

Ruixuan Jiang

M F Bas Janssen

A Simon Pickard

Affiliations

Soon will be listed here.

Abstract

Purpose: Normative scores (norms) allow for comparisons between population(s) of interest and the general population, which is useful for burden of disease studies and cost-effectiveness analysis. The primary aim of this study was to estimate US visual analogue scale (EQ VAS) and utility-based norms for the EQ-5D-5L using the face-to-face sample. The secondary aim was to compare norms estimated in the face-to-face and online populations.

Methods: This study estimated population norms from two general population surveys: (a) face-to-face and (b) online. In these surveys, respondents provided their health state using the EQ-5D-5L health classifier and the EQ VAS. Descriptive statistics, including mean, standard deviation (SD), 95% confidence interval, and median for the 5L utility and EQ VAS were estimated for each sample and across relevant respondent characteristics to serve as the basis for US EQ-5D-5L norms RESULTS: Face-to-face sample respondents (n = 1134) were representative of the US adult general population. In this sample, mean (SD) utility decreased with increasing age until age 45 or greater (age 45-54: 0.816 (0.249) age 55-64: 0.815 (0.243) age 65-74: 0.824 (0.217) age 75 + : 0.811 (0.218)). With increasing age, more problems were reported on all dimensions except anxiety/depression; a smaller proportion of respondents age 65 and older reported problems with anxiety/depression (23.8%) as compared to the youngest respondents (42.1%). Online (n = 2018) mean utility and EQ VAS values were consistently lower than the face-to-face sample.

Conclusions: The availability of US EQ-5D-5L norms facilitates interpretation and understanding of general population and patient health.

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