Search found 16 items
This research prospectively evaluated a machine learning algorithm that identifies candidates for neurologic surgery to control epilepsy.
This project will evaluate and compare different tools within electronic health records to assist pediatric primary care clinicians with providing higher quality childhood obesity care to help slow weight gain in children with obesity.
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 studied the influence of social networks on technology implementation and found that clinicians’ networks influence beliefs and use of the electronic medical records.
This project developed and piloted a patient-centered clinical decision support tool that was used in emergency department management of minor head injury and found high patient and clinician satisfaction and usability.
This project designed a shared decisionmaking support aid for vaginal birth after Caesarean section and concluded that the tool was feasible to implement for a diverse patient population.
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 developed and validated a new disability diagnostic tool that allowed emergency department physicians to connect patients to better healthcare referrals and proper long-term care services.