This research will explore whether providing clinicians with contextual information at the point of care through the use of clinical decision support can reduce contextual errors, improve patient healthcare outcomes, and reduce misuse and overuse of medical services.
This project will develop a method to use video captured electronic health record interactions to analyze the context around medication errors, identify design elements that contributed to the errors, and make design recommendations to mitigate those errors.
This project will enhance novel algorithms for matching patient health information across data sources, implement them, and evaluate their accuracy.
The goal of this project is to design and test an information technology called Power to the People to support self-care management among older patients with chronic heart failure.
The goal of this project is to develop and evaluate an air traffic control-like command center for operating rooms.
This project will develop and evaluate an electronic health record-embedded clinical decision support tool that draws upon the strength of analytical and naturalistic decision-making to optimize the use of blood cultures in critically ill children.
This project will develop a clinical decision support tool for the perioperative setting.
This project aims to improve access to high quality mental health services for diverse populations by implementing asynchronous telepsychiatry consultations combined with automated online interpreting.
The project will develop and test a large set of alerts at two large health systems to demonstrate that alerts can help prevent wrong-drug and wrong-patient errors and improve the completeness of the problem list.
This study will design a user-centered smartphone application linked to a smart pill box with the goal of improving medication adherence for people living with HIV.