- Remove Cardiovascular Disease filter Cardiovascular Disease
Search found 31 items
The aim of this research is to implement a clinical decision support tool to provide clinicians patient-specific and evidence-based treatment recommendations regarding the recognition and management of high blood pressure and hypertension in children and adolescents.
This research will implement a personalized and electronically integrated shared clinical decision support system for left ventricular assist devices in patients with advanced heart failure.
This research will support the development and testing of two electronic care plan applications and implementation guide for managing persons with chronic kidney disease and at least one additional chronic condition.
This research will create patient-centered, interoperable, shareable clinical decision support tools that will support providers and patients in making patient-centered decisions about management of hypertension.
This research will estimate the cost-effectiveness of pharmacogenomics clinical decision support alerts and create a tool that provides estimates of the value of developing and implementing them.
This research aims to create, develop, and implement a decision support tool that clarifies the risk tradeoffs for anticoagulation in atrial fibrillation.
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 research will demonstrate the use of standards, including SMART on FHIR, combined with service-oriented architecture to bring vendor-agnostic clinical decision support (CDS) tools into commercial electronic health records, and provide evidence for how to implement validated CDS for important clinical domains, pulmonary, and venous thromboembolism, including for patients with COVID-19.
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 research developed a set of mHealth tools capable of collecting health behavior information with the hope that providing clinical feedback on these behaviors will reduce obesity and improve health behaviors among at-risk families.