Geographic Socioeconomic Influences on Disease Activity in Rheumatoid Arthritis in an Academic and Safety Net Hospital System - Joseph Kim; Song Zhang; Ang Gao; Donglu Xie; Salahuddin Kazi; David R. Karp; Christie M. Bartels; E. Blair Solow (ACR Open Rheumatology)
Objective The objective of this study was to analyze the impact of the Area Deprivation Index (ADI) on disease activity and cardiovascular comorbidity in rheumatoid arthritis (RA). Methods A retrospective analysis of adult patients with RA was conducted to highlight differences in academic and safety net hospital clinics. Demographics, RA medication history, patient portal engagement, primary care presence, emergency or inpatient visits, RA disease activity and functional scores, Charlson Comorbidity Index (CCI), and cardiovascular disease (CVD) presence were captured. The ADI rank was assigned using nine‐digit zip codes. Patients were stratified by the upper versus lower ADI decile group and matched by age, sex, race, ethnicity, insurance, and CCI using propensity score analysis. Results Patients with RA from the academic practice (n = 542) and the safety net hospital (n = 496) were assessed. In the academic cohort, those with high ADI scores (>8, more deprivation) had higher RA disease activity scores (Routine Assessment of Patient Index Data 3 mean ± SD: high 13.83 ± 6.94 vs low 11.17 ± 7.37, P < 0.0001; Clinical Disease Activity Index mean ± SD: high 11.97 ± 11.74 vs low 9.40 ± 7.97, P < 0.05), more functional impairment (Multidimensional Health Assessment Questionnaire mean ± SD: high 2.99 ± 2.29 vs low 2.34 ± 2.23, P < 0.01), lower MyChart use (P < 0.001), and different smoking history (P < 0.01) compared to those with low ADI scores (<3, less deprivation). In the safety net cohort, there was a statistically significant difference only in smoking status (P < 0.05). CVD was not significantly different in either cohort. Conclusion The absence of differences in RA disease activity and functional impairment in patients suggests that the ADI may not be as effective at predicting RA disease activity specifically in a safety net health care context. Identifying the discrepancies between the two systems may elucidate areas of improvement for patient care.