This project developed PocketBuddy, a handheld technology for aging adults to assist in caregiving activities, monitoring the well-being of both the caregiver and the person being cared for, and capturing information on the home environments.
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.
Evaluated the completeness and accuracy of information on symptoms, disease conditions, medications, and allergies generated by parents using a patient-centered health technology called ParentLink, compared to information documented by emergency department physicians and nurses; and assessed ParentLink's impact on patient safety and quality.
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 informed Stage 3 Meaningful Use requirements by evaluating metrics related to identification of delirium in real time and improving accuracy of the problem list, thus potentially improving care for patients with delirium.
This research prospectively evaluated a machine learning algorithm that identifies candidates for neurologic surgery to control epilepsy.
This study examined parent and provider experiences and care costs for in-person, hybrid, and all-virtual pediatric physiatry models in rural and underserved communities, concluding that the hybrid model—where therapists and patients are onsite and the pediatric physiatrist is present via telehealth—offers a high-quality, acceptable, and cost-effective alternative.
