Johns Hopkins University
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 evaluate the safety, usability, and impact of an e-prescribing standard on adverse drug events related to erroneously dispensed medications.
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 developed and evaluated a clinical decision support system that effectively communicated genomic data to clinicians to improve healthcare decision making.
This project developed and pilot-tested a novel, outcomes-based emergency department triage tool and found that risk stratification and waiting times were improved for some patients.
This project seeks to develop an understanding of the cognitive work of clinician teams and family members involved in pediatric trauma care transitions in order to design usable and useful health information technologies.
This project developed and validated a 30-day readmission risk prediction model that incorporated data from a health information exchange.
This project evaluated the feasibility of two Stage 3 Meaningful Use Care Coordination measures and provided feedback to policymakers and providers for their improvement.