Journal of clinical rheumatology : practical reports on rheumatic & musculoskeletal diseases · 2026
Patterns of Residential Mobility by Social Vulnerability Among Individuals With Rheumatic and Musculoskeletal Conditions.
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Santacroce Leah M, Feldman Candace H
Аннотация
OBJECTIVE: Area-level factors such as neighborhood poverty affect the health of individuals with rheumatic conditions. The connection of area-level data with health data via electronic health records (EHR) often relies upon the most recent patient address. We investigated longitudinal address history to understand mobility to areas with differing degrees of social vulnerability.
METHODS: We identified individuals with rheumatic or musculoskeletal conditions receiving rheumatology care in a multihospital health care organization (2019-2024) in this cohort study. We geocoded available addresses for everyone over 5 years and merged them with the census tract-level Social Vulnerability Index. We used multinomial regression to investigate associations with patient characteristics and movement to areas with different SVIs.
RESULTS: Among 10,376 individuals, 2563 (25%) moved ≥1 time. 504 (20%) moved to a census tract with higher vulnerability, and 420 (16%) moved to a lower one. Increased likelihood of moving to an area with higher vulnerability was associated with being Black (OR 3.43, 95% CI: 2.13-5.54) or a Medicaid beneficiary (OR 1.87, 95% CI: 1.34-2.61). Decreased likelihood of moving to a lower vulnerability area was associated with being Black (OR: 0.51, 95% CI: 0.31-0.83) or a Medicaid beneficiary (0.66, 95% CI: 0.45-0.98).
CONCLUSIONS: Address histories from the EHR can provide a more nuanced understanding of area-level factors, especially for Black and lower-income individuals with rheumatic conditions. This information may help inform hospital-wide initiatives to identify patients who may be at higher risk for negative health outcomes based on their residential mobility.
METHODS: We identified individuals with rheumatic or musculoskeletal conditions receiving rheumatology care in a multihospital health care organization (2019-2024) in this cohort study. We geocoded available addresses for everyone over 5 years and merged them with the census tract-level Social Vulnerability Index. We used multinomial regression to investigate associations with patient characteristics and movement to areas with different SVIs.
RESULTS: Among 10,376 individuals, 2563 (25%) moved ≥1 time. 504 (20%) moved to a census tract with higher vulnerability, and 420 (16%) moved to a lower one. Increased likelihood of moving to an area with higher vulnerability was associated with being Black (OR 3.43, 95% CI: 2.13-5.54) or a Medicaid beneficiary (OR 1.87, 95% CI: 1.34-2.61). Decreased likelihood of moving to a lower vulnerability area was associated with being Black (OR: 0.51, 95% CI: 0.31-0.83) or a Medicaid beneficiary (0.66, 95% CI: 0.45-0.98).
CONCLUSIONS: Address histories from the EHR can provide a more nuanced understanding of area-level factors, especially for Black and lower-income individuals with rheumatic conditions. This information may help inform hospital-wide initiatives to identify patients who may be at higher risk for negative health outcomes based on their residential mobility.