Electronic Health Record-linked Decision Support for Communicating Genomic Data
This project developed and evaluated a clinical decision support system that effectively communicated genomic data to clinicians to improve healthcare decision making.
This project developed and evaluated a clinical decision support system that effectively communicated genomic data to clinicians to improve healthcare decision making.
This research study addressed the overuse of blood cultures to diagnose sepsis by developing an electronic health record-embedded clinical decision support tool that draws upon the strengths of analytical and naturalistic decision making.
This research developed strategies to optimize CancelRx implementation and measured its impact on dispensing errors and patient outcomes.
This research will develop and evaluate an artificial intelligence-driven clinical decision support system to detect and manage acute kidney injury in the emergency department.
This research will lead to the creation of a digital healthcare equity framework and accompanying guide to assist those in creating digital solutions.
The annual Conference on Health IT and Analytics (CHITA) facilitates the development of research and implementation lessons; fosters relationships among academics, policymakers, and practitioners; and helps disseminate research and train the next generation of health IT and analytics researchers with diverse backgrounds to improve healthcare quality, efficiency, and equity.
This research will enhance an augmented reality headset used to provide real-time feedback on pediatric chest compressions. Researchers will evaluate the usability and user experience of the augmented reality cardiopulmonary resuscitation tool in an international multicenter randomized simulation study, with the aim of improving the quality of chest compressions and saving lives.