Search found 23 items
This research will apply innovative health information technology strategies to improve methods for systematic collection and use of patient-reported outcomes in clinical care for those with multiple chronic conditions using person-specific patient-reported outcomes.
This research prospectively evaluated a machine learning algorithm that identifies candidates for neurologic surgery to control epilepsy.
This study analyzed and modeled information requirements, decision making, and workflow of homecare nurses admitting patients leading to the development, review, and dissemination of information technology design and implementation recommendations in this setting.
This project designed and conducted a usability evaluation of dashboards that provide feedback to home care nurses to improve the care of patients with chronic heart failure, and found that the dashboard prototype had high usability and was evaluated positively by users.
This project tested a mobile health application’s impact on reducing readmissions among patients with cirrhosis within 30 days of hospital discharge, and found it to be usable and feasible.
This project developed a tool to promote activation, communication, engagement, and self-management of pediatric blood and marrow transplant patients and their parents and found that patient-centric tools can successfully engage caregivers in hospital care.
This study aimed to improve care transitions for low-income patients with multiple chronic conditions using health information exchange, and found significant reductions in inpatient and emergency department utilization.
This project developed a decision making tool for patients with asymptomatic carotid stenosis and concluded that it was feasible to implement in clinical practice.
This research studied the healthcare information needs of elders and their family caregivers and developed an online platform to allow this group to share health information.
This research demonstrated a shared decision-making program influencing Crohn’s disease patients’ choice of therapy and decision quality.