What Determines the Shape of an EQ-5D Index Distribution?

David Parkin, Nancy Devlin, Yan Feng

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)

Abstract

BACKGROUND: EQ-5D-3L index scores in patient and general populations typically have a nonnormal distribution, divided into 2 distinct groups. It is important to understand to what extent this is determined by the way that the EQ-5D-3L index is constructed rather than by the true distribution of ill health.

OBJECTIVE: This paper examines the determinants of the "2 groups" distribution pattern and the extent to which this pattern is attributable either to the EQ-5D-3L classification system used to create health state profiles or to the weights applied to profiles.

METHODS: Data from the English NHS PROMs program (hip and knee replacements and varicose vein and hernia repairs) and from a study of 2 chronic conditions (asthma and angina) were used to compare the distributions of EQ-5D-3L index scores with distributions from which weights have been stripped; profile data decomposed into their constituent dimensions and levels; a condition-specific index; and using weights from different countries, based on both time tradeoff and visual analogue scale.

RESULTS: The EQ-5D-3L classification system generates differences between patients with the same condition in respect of dimensions that are mainly observed at level 2 or 3. The weights commonly used to calculate the index exacerbate this grouping by placing a larger weight on level 3 observations, generating a noticeable gap in index scores between the groups.

CONCLUSIONS: Analyzing EQ-5D profile data enables a better understanding of the resulting distribution of EQ-5D scores. The distinctive shape observed for these distributions is the result of both the classification system and the weights applied to it.

Original languageEnglish
Pages (from-to)941-951
JournalMedical Decision Making
Volume36
Issue number8
Early online date25 Apr 2016
DOIs
Publication statusPublished - 1 Nov 2016

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