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This project will apply machine learning against a large data set to develop a model to both understand and predict surgical cancellations on individual pediatric patients at two pediatric surgical sites.
This project tested a pediatric voice therapy telehealth system and found that it was feasible to implement and well accepted by children and their families.
This project utilized input from patients and clinicians in order to develop three test versions of an after visit summary (AVS), and employed a randomized controlled trial to evaluate the various versions against a standard AVS.