Impact of Social Determinants of Health on Patients with Complex Diabetes Who Are Served by National Safety-Net Health Centers

Objective: Recent research demonstrates an increased need to understand the contribution of social determinants of health (SDHs) in shaping an individual's health status and outcomes. We studied patients with diabetes in safety-net centers and evaluated associations of their disease complexity, demographic characteristics, comorbidities, insurance status, and primary language with their HbA1c level over time.

Methods: Adult patients with diabetes with at least 3 distinct primary care visits between January 1, 2006, and December 31, 2013, were identified in the CHARN data warehouse. These patients were categorized into 4 groups: those without a diagnosis of cardiovascular disease (CVD) or depression; those with CVD but not depression; those with depression but not CVD; and those with CVD and depression. Charlson score; demographic characteristics such as age, sex, and race/ethnicity; and SDHs such as primary language and insurance status were used as predictors. The outcome measure was HbA1c. Hypothesis testing was conducted using 3-level hierarchical linear models.

Results: Baseline HbA1c differed significantly across the 4 diabetes groups and by race/ethnicity. The amount of HbA1c change over time differed by insurance status. Patients who were continuously insured tended to have lower baseline HbA1c and a smaller increase. Chinese-speaking patients tended to have lower baseline HbA1c but a larger increase over time compared with English speakers. There were various unexpected associations: compared with the diabetes-only group, mean HbA1c tended to be lower among the other more complex groups at baseline; women tended to have lower measures at baseline; older age and higher Charlson scores were associated with lower HbA1c.

Conclusions: There is still unexplained variability relating to both baseline HbA1c values and change over time in the model. SDHs, such as insurance status and primary language, are associated with HbA1c, and results suggest that these relationships vary with disease status among patients with diabetes in safety-net centers. It is important to recognize that there are complex relationships among demographic and SDH measures in complex patients, and there is work to be done in correctly modeling and understanding these relationships. We also recommend prioritizing the collection of SDH and enabling services data for safety-net patients that would be instrumental in conducting a more comprehensive study.