AIRnyc has qualitative and quantitative processes to assess a patient's risk. The quantitative model uses machine learning techniques to predict future medical utilization. Our data-driven practices, combined with on the ground experience, are highly sensitive to the needs of the families we serve. In tandem with an evidence-based approached, analytical capacity is a central, defining attribute of AIRnyc's model, one that contributes to continuous quality improvement (CQI), root cause analysis (RCA), and cost-effectiveness.