Differences in Longitudinal Disease Activity Between Research Cohort and Noncohort Participants with Rheumatoid Arthritis Using Electronic Health Record Data. Issue 2 (10th April 2019)

• Record Type: Journal Article
• Authors: Gianfrancesco, Milena A.; Trupin, Laura; McCulloch, Charles E.; Shiboski, Stephen; Schmajuk, Gabriela; Yazdany, Jinoos
• Is Part Of: ACR open rheumatology. Volume 1:Issue 2(2019)
• Page Start: 113
• Page End: 118
• Publication Date: 2019-04-10
• Subjects: cohort studies -- epidemiology -- rheumatoid arthritis; Rheumatology -- Periodicals; 616.723005
• DOI: 10.1002/acr2.1017
• Languages: English
• ISSNs: 2578-5745

Abstract

ABSTRACT: Objective: Research using electronic health records (EHRs) may offer advantages over observational prospective cohort studies, including lower costs and a more generalizable patient population; however, EHR data may be more biased because of the high prevalence of missing data. We took advantage of a unique clinical setting in which all patients with rheumatoid arthritis (RA) were asked to participate in a longitudinal cohort study that would examine potential biases of EHR vs. prospective cohort designs in assessment of disease outcomes, but only some chose to participate. Methods: For individuals both participating in the cohort ("cohort, " n = 187) and not participating ("noncohort, " n = 190), we retrieved data regarding RA disease activity and other sociodemographic and clinical factors from data recorded in the EHR between 2013 and 2017. We compared the prevalence of missing data between groups and studied differences in disease activity measures over time. Results: Disease activity measures were less likely to be missing for cohort participants compared with noncohort participants (0.2%‐13% vs. 2%‐22%, respectively). No significant differences were present at baseline with respect to race/ethnicity or disease activity measures between groups. However, black, non‐Hispanic race/ethnicity was associated with worse longitudinal disease activity compared with white, non‐Hispanic individuals in noncohort participants ( β = 6.47, P =0.03) but not in cohort participants ( β = −0.10, P = 0.97) ( P interaction = 0.09). Conclusion: Findings suggest that data derived from the EHR were comparable to a cohort across some variables but captured racial/ethnic disparities in long‐term outcomes not observed in the cohort study. Research utilizing EHR data in conjunction with cohort studies may provide new opportunities for studying health disparities.