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This research aims to develop and evaluate a clinical decision support strategy to promote influenza vaccination among children who are hospitalized with the goal to identify insights that broadly apply to clinical decision support for health maintenance interventions in pediatric acute care settings.
This project will develop and evaluate the impact of the Prevent Diabetes Mellitus Clinical Decision Support on clinical outcomes, healthcare process measures, and associated costs.
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 develop and disseminate an innovative communication system to identify and mitigate health risks for young African American women before pregnancy as a means of reducing health disparities in birth outcomes.
This project will design natural language processing algorithms to extract data from free text notes on autism spectrum disorders in electronic health records, and demonstrate the feasibility and usefulness of this approach.
This project developed and pilot tested an electronic after-visit summary (AVS) that incorporated evidence-based strategies for communicating printed health information to patients and determined best practices for future AVS development.
This project developed and tested a smartphone application of an alcohol intervention for college freshmen and found that it worked as well as a traditional in-person approach.
This research created and evaluated the impact of immunization reminders using information from an electronic health record combined with an immunization information system.
This project will integrate clinical decision support into providers’ workflow in neonatal intensive care units to deliver evidence-based guidelines for early recognition and prevention of necrotizing enterocolitis, a serious complication threatening the life of fragile premature infants.
This project applied a user-centered design process to understand the needs and attitudes for sharing patient-collected lifelog data with providers to improve management and decision making.