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

Med Decis Making. 2016 Nov;36(8):941-51. doi: 10.1177/0272989X16645581. Epub 2016 Apr 25.

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.

Keywords: EQ-5D; health state preferences; health-related quality of life; utilities; valuations.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Chronic Disease / psychology
  • Clinical Decision-Making
  • Data Interpretation, Statistical*
  • Health Status*
  • Humans
  • Models, Statistical
  • Patient Preference / psychology*
  • Psychometrics
  • Quality of Life*
  • State Medicine
  • Surgical Procedures, Operative / psychology
  • United Kingdom