Clustering of self-reported social and environmental risk factors identifies vulnerable subgroups with increased asthma morbidity.

Background: Social determinants of health (SDOH) and environmental triggers contribute to risk of asthma exacerbations. Electronic health record data rarely capture complete SDOH and asthma trigger information, thereby limiting comprehensive risk factor assessments absent additional data sources. Objective: We collected detailed SDOH and trigger data from patients with asthma who were identified from electronic health records to better understand modifiable risk factors contributing to risk of asthma emergency department (ED) visits. Methods: We invited patients with asthma identified through the Penn Medicine electronic health record to complete an online questionnaire covering SDOH, asthma triggers, and asthma history. Zero-inflated Poisson regression models were fit to identify factors associated with ED visits for asthma, and hierarchical agglomerative clustering was used to explore underlying patterns in the data. Results: Among 974 survey respondents, 206 reported one or more asthma-related ED visit in the last year. Nearly all SDOH and asthma trigger variables were significantly associated with asthma ED visits in univariable models, but most of these effects were strongly attenuated in multivariable regression models. The effect of race, however, remained strong in both models. Conclusion: Self-reported SDOH and asthma trigger data are useful to identify subpopulations at highest risk for adverse asthma outcomes.