Patient Engagement

This research explores using natural language processing and generative AI to capture and structure social determinants of health from patient narratives, aiming to improve data completeness and quality, enhance clinical decision support, and reduce the manual burden on clinical staff in routine care.

The study will create, implement, and test a patient-centric web app to support older adults with chronic conditions in comprehending, managing, and acting upon their lab test results.

This research will evaluate the safety, usability, diagnostic, and triage accuracy of a popular symptom checker app and new diagnostic algorithms, and their ability to affect patients’ decisions to seek care, particularly for transient ischemic attacks and stroke.

This research will adapt an evidence-based digital health intervention for attention deficit hyperactivity disorder in children to improve communication and care coordination across multiple points of care.

This research will utilize user-centered design to develop and implement a self-management education and support module called Support-Engage-Empower-Diabetes (SEE-Diabetes) to improve diabetes management in older adults.

This study explored the use of and experiences with sharing inpatient notes during pediatric oncology hospitalization between parents and clinicians, with findings suggesting its potential to positively impact parent engagement and understanding in pediatric inpatient care and providing an opportunity to identify potential patient safety issues.

This research will examine the factors affecting cancer patients’ use of an electronic patient safety event reporting system to communicate adverse medication-related events to their care team.