Search found 22 items
This research will further disseminate a currently used clinical decision support tool to identify patients at risk for a life threatening, uncommon cardiac arrhythmia.
This project proposes a novel proactive system to reduce alert burden and thereby increase attention to situations in which patient safety is at risk.
This study will test the hypothesis that low-income, disadvantaged patients can provide high-quality patient-generated health data and patient-reported outcomes through commercial technologies, and that these data can be used to improve healthcare quality and delivery.
This project will design natural language processing algorithms to extract data from free text notes on autism spectrum disorders in electronic health records, and demonstrate the feasibility and usefulness of this approach.
This project developed a natural language processing electronic health record search tool that automatically identifies and ranks relevant clinical information based on a patient’s presenting complaint within the emergency department setting.
This project will develop a mobile health application to improve screening, intervention, and referrals in the care of pregnant women.
This project developed a patient-centric tool called the Surgical Risk Preoperative Assessment System to estimate the risk of adverse operative outcomes.
This project developed patient-tailored relevant warnings about drug-drug interactions and found that it reduced irrelevant alerts.
This project will integrate clinical decision support into providers’ workflow in neonatal intensive care units to deliver evidence-based guidelines for early recognition and prevention of necrotizing enterocolitis, a serious complication threatening the life of fragile premature infants.
This project developed, implemented, and assessed a patient data collection and clinician feedback system for depression care management in primary care practices, and found improvements in patient medication filling and adherence.