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This project developed a natural language processing electronic health record search tool that automatically identifies and ranks relevant clinical information based on a patient’s presenting complaint within the emergency department setting.
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 study assessed the usability and impact of inpatient portals on patient experience, engagement, and perceptions of care.
This project developed, implemented, and assessed a patient data collection and clinician feedback system for depression care management in primary care practices, and found improvements in patient medication filling and adherence.
This project evaluated the usability of medication fulfillment data obtained from electronic health records and piloted a clinical decision support tool that alerted physicians to potential hypertensive medication adherence lapses.
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.