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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 study assessed the usability and impact of inpatient portals on patient experience, engagement, and perceptions of care.
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.
This project used a mixed-method approach to investigate the validity of using electronic health record data for diabetes performance measures.
This project looked at the ability of EHRs to facilitate patient outcomes tracking, improve provider communication, reduce medical errors, and improve quality of care.
Developed, implemented, and evaluated a cooperative effort for using health IT to facilitate a continuum of appropriate medical and developmental care, from the time infants are admitted to Neonatal Intensive Care Units (NICUs), through the transition process to community-based health care services for infants most at-risk for long-term neurodevelopmental problems.