Search found 27 items
This project will use Learning Health System methods to systematically apply U.S. Preventive Services Task Force’s evidence-based recommendations with the goal of advancing individualized precision prevention.
This project will use machine learning to enhance an existing sepsis clinical decision support tool to improve the early detection of sepsis.
This project will develop and test the effectiveness of a mobile application to help patients with hypertension reduce their dietary sodium intake by using mobile notifications at grocery stores and restaurants.
This project examined the prevalence of variation in electronic health record documentation in physician practice, its causes, effects, and strategies to mitigate its potential for harm.
This project tested the impact of a training module that teaches clinicians how to best communicate with patients in the presence of an electronic health record and found improvements in provider communication skills, but no impact on patient outcomes.
This project developed a diabetes data visualization mobile application for adolescents and found that clinical and contextual data provided greater opportunity for self management and problem solving.
The purpose of this study is to describe how communication technologies make it easier or more difficult for nurses and physicians to communicate with each other, with a goal of finding ways to support effective communication.
This study focuses on the use of eHealth in cancer survivors and will identify determinants of eHealth activity, provide insight into the role of eHealth in survivors’ overall personal health information management, and establish survivor-centered design principles for optimized eHealth tool development.
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 project explored whether the use of data from pain management practices can be used to develop more robust evidence-based approaches to chronic pain management.