Brigham and Women's Hospital

This research aims to improve the early detection of venous thromboembolism in primary and urgent care by using mixed methods (stakeholder interviews and surveys, electronic health records, and machine learning) to better understand missed and delayed diagnoses, identify risk factors, and develop tools to enhance patient safety.

This research evaluates the adoption and impact of three electronic health record-optimization interventions—scribes, advanced team-based inbox management, and artificial intelligence-assisted messaging support—on primary care physicians' time, wellbeing, and patient outcomes, with the goal of identifying effective strategies to improve physician satisfaction and care quality and to reduce healthcare costs.

This research will create clinical decision support artifacts for three patient-centered outcomes research guidelines around advanced diagnostic imaging using standards to allow them to be shareable, interoperable, and scalable; and implement them in different workflows and settings measuring their impact. 

This research will refine a current health information exchange platform to improve data exchange for inter-hospital transfers, evaluate its impact, and create a dissemination toolkit so that others may adopt this model.

This study will develop, evaluate, and disseminate a multicomponent intervention including a mobile health application and digital navigator training to support safe care transitions for patients with multiple chronic conditions.

This research will use digital health tools leveraging patient-reported outcomes and data from electronic health records to engage individuals with multiple chronic conditions to improve understanding of individualized risk of adverse events during care transitions.