Reweighting to address nonparticipation and missing data bias in a longitudinal electronic health record study

We examined whether weighting techniques could account for longitudinal differences in disease activity by race/ethnicity between research participants and nonparticipants with rheumatoid arthritis (RA).

We included 377 patients with RA from a public hospital in San Francisco, CA. We estimated the probability of not enrolling in a research study by constructing weights using inverse probability weighting. Disease activity over time by race/ethnicity was analyzed across the entire patient population and among research participants only using multivariable mixed-effects models.

There were no differences in RA disease activity scores between research participants and nonparticipants at baseline; however, longitudinal differences in disease activity between research participants and nonparticipants were found by race/ethnicity. Weighting research participants in accordance with sociodemographic and clinical characteristics of the nonparticipant population did not result in any meaningful changes in disease activity by race/ethnicity over time.

In our study of patients with RA, inverse probability weighting using select sociodemographic and clinical variables was not sufficient to account for longitudinal disease activity differences by race/ethnicity between research participants and nonparticipants.