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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 will enhance an existing Web-based portal, myADHDportal.com, to integrate behavioral tools alongside existing medication management tools for attention deficit hyperactivity disorder (ADHD).
The project team will develop a set of mHealth tools capable of collecting health behavior information and evaluate whether providing clinical feedback on these behaviors reduces obesity and improves health behaviors among at-risk families.
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.
The project sought to create a generalizable system to facilitate detection and clinician reporting of vaccine adverse events and found that it is possible to automatically detect adverse events in defined ways, and to electronically report them.
This project evaluated whether an interactive voice response system used by parents prior to routine health maintenance visits could improve parental activation, the comprehensiveness of care provided, and medication safety.
This project evaluated the Pharmaceutical Safety Tracking (PhaST) system, which monitors medication safety in children and adolescents who are taking antidepressants.
Systematically assessed improvements in patient safety and experience of care associated with implementation of four decision support function embedded in an electronic health record: 1) the influence of weight based dosing on pediatric adverse drug events; 2) the influence of a test result tracking system on appropriate followup of ordered tests; 3) the influence of automated reminders on symptom monitoring and medications for children with asthma and attention deficit disorder.