Sociomarkers to Predict Asthma Control and Emergency Room Visits (SPACER)

The overall objective of this project is to improve management and reduce morbidity associated with asthma through better classification of illness severity and future risk. The central hypothesis is that enhancing asthma risk prediction through estimation of social and financial hardships, incorporation of temporal and environmental data, and application of machine learning in a health plan setting will add significant value in helping care management programs identify patients for interventions to moderate their social and clinical risk. The long-term goal of this study is to establish a research program focused on development of computational models for predicting socially medicated clinical outcomes.