Quasi-Experimental Designs for Learning Systems: A growing number of systems, including hospitals and insurance companies, aim to derive knowledge from internal data to improve their day-to-day operations. Amy Cochran (Mathematics and Population Health Sciences), Gabriel Zayas-Caban (Industrial and Systems Engineering) and Brian Patterson (Berbee Walsh Department of Emergency Medicine) will develop a causal inference framework for estimating the effects of interventions on these systems and provide algorithms to guide their use of risk prediction models in their operations, with the goal of improving services and reducing costs. Click here for more information on the award.