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.
The goal of this project is to develop and evaluate an air traffic control-like command center for operating rooms.
This project created a natural language processing-enabled clinical decision support system to pull patient information and determine recommendations for cervical cancer screening, and demonstrated improvement in overall screening and surveillance rates.
This project evaluated SMARxT, web-based education modules designed to teach resident physicians how to effectively navigate and counteract pharmaceutical-sponsored messaging within technology.
This project developed and evaluated a clinical decision support system that effectively communicated genomic data to clinicians to improve healthcare decision making.
This research investigated how electronic health record use affected clinical workflow, efficiency, and quality of care in the emergency department, and developed recommendations for future stages of Meaningful Use.
This project will analyze and model the information requirements, decisionmaking, and workflow of homecare nurses admitting patients and characterize if and how health information technology systems support their needs.
This project analyzed secondary data to identify factors associated with timely opening of electronic health record-based asynchronous alerts, timely response to the alerts, and patient outcomes.
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 study examined clinical decision task complexity to guide the design of innovative clinical decision support to for high-level reasoning in complex decision tasks.