Kenneth McKinley, M.D., is junior faculty with a research focus in predictive analytics. At Children’s National, Dr. McKinley has built on research from his clinical fellowship, focusing on the application of complex computational models to predict the impact of system changes on pediatric Emergency Department throughput. He is now focused on the application of machine learning algorithms to develop risk prediction models for specific pediatric populations that present to the Emergency Department, including patients presenting with chief complaints related to sickle cell disease, asthma, or behavioral health. Febrile children with sickle cell disease represent a particular challenge in the Emergency Department because fever is such a common problem in childhood. Recommendations developed before the advent of conjugate vaccines continue to drive clinical practice in this high-risk population. Children with asthma or behavioral health complaints often require extended periods of emergency evaluation. By creating robust risk prediction models for patients presenting with these complaints, Dr. McKinley’s work aims to enhance care for these patients, improve patient throughput generally, and help address the national problem of ED crowding.