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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.
The project team developed a technical brief on the current literature around core functionalities for pediatric electronic health records to describe current practice and to provide a framework for future research.
The project team successfully developed a knowledgebase specific to medication management for children. The tools created included an algorithm for rounding of medication doses and a compounded medication knowledgebase.
This project evaluated the Pharmaceutical Safety Tracking (PhaST) system, which monitors medication safety in children and adolescents who are taking antidepressants.