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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.
Implemented and evaluated a voluntary system for reporting medical errors and adverse drug events in eight small rural hospitals; identified barriers to technology, described the epidemiology and root causes of the errors, formulated quality-improvement interventions, and disseminated the results of the project.