Retrospectively Collected EQ-5D-5L Data as Valid Proxies for Imputing Missing Information in Longitudinal Studies

Value Health. 2021 Dec;24(12):1720-1727. doi: 10.1016/j.jval.2021.07.007. Epub 2021 Sep 10.


Objectives: Studies face challenges with missing 5-level EQ-5D (EQ-5D-5L) data, often because of the need for longitudinal EQ-5D-5L data collection. There is a dearth of validated methodologies for dealing with missing EQ-5D-5L data in the literature. This study, for the first time, examined the possibility of using retrospectively collected EQ-5D-5L data as proxies for the missing data.

Methods: Participants who had prospectively completed a 3rd month postdischarge EQ-5D-5L instrument (in-the-moment collection) were randomly interviewed to respond to a 2nd "retrospective collection" of their 3rd month EQ-5D-5L at 6th, 9th, or 12th month after hospital discharge. A longitudinal single imputation was also used to assess the relative performance of retrospective collection compared with the longitudinal single imputation. Concordances between the in-the-moment, retrospective, and imputed measures were assessed using intraclass correlation coefficients and weighted kappa statistics.

Results: Considerable agreement was observed on the basis of weighted kappa (range 0.72-0.95) between the mobility, self-care, and usual activities dimensions of EQ-5D-5L collected in-the-moment and retrospectively. Concordance based on intraclass correlation coefficients was good to excellent (range 0.79-0.81) for utility indices computed, and excellent (range 0.93-0.96) for quality-adjusted life-years computed using in-the-moment compared with retrospective EQ-5D-5L. The longitudinal single imputation did not perform as well as the retrospective collection method.

Conclusions: This study demonstrates that retrospective collection of EQ-5D-5L has high concordance with "in-the-moment" EQ-5D-5L and could be a valid and attractive alternative for data imputation when longitudinally collected EQ-5D-5L data are missing. Future studies examining this method for other disease areas and populations are required to provide more generalizable evidence.

Keywords: EQ-5D-5L; longitudinal studies; missing data imputations; retrospective data collection.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Aged, 80 and over
  • Bias*
  • Data Collection*
  • Female
  • Health Surveys*
  • Humans
  • Longitudinal Studies*
  • Male
  • Middle Aged
  • Retrospective Studies