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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 developed, implemented, and evaluated a voice-generated enhanced electronic note system and found that it did not improve the time to finalize notes or clinician satisfaction.
This project aimed to capture and understand how clinical work is actually done, and then to analyze how the efficiency and quality of care could be measurably improved through health information technology.
This project sought to reduce the use of emergency department services for non-urgent care by improving access to primary care physicians for Medicaid patients via the electronic medical record.