This research will lead to the creation of a digital healthcare equity framework and accompanying guide to assist those in creating digital solutions.
Johns Hopkins University
Transforming Kidney Care in the Emergency Department Using Artificial Intelligence-Driven Clinical Decision Support
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.
Development of a Clinical Decision Support Tool for Facilitating Naturalistic Decision Making and Improving Blood Culture Utilization
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 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.
Care Transitions and Teamwork in Pediatric Trauma: Implications for Health Information Technology Design
This research used a human-centered design approach to understand the cognitive work of clinical teams involved in pediatric trauma care transitions that informed the development of two prototypes for digital healthcare solutions that support clinicians caring for pediatric trauma patients.
A Community Health Information Exchange-based Hospital Readmission Risk Prediction & Notification System
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.