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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 develop, test, and evaluate a vendor-agnostic platform for clinical decision support rules that can be made available to any commercial electronic health record.
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.
This project developed and tested a mobile health application for a centralized, pharmacist-managed cardiovascular risk service to improve patient engagement in self-management of cardiovascular risk.
This project will study the usability of electronic health records (EHRs) by cardiac care physicians and nurses to develop a set of best practices in EHR design to inform vendors of the wants and needs of clinical providers.
This project designed and tested a smartphone patient application to detect vascular surgical site infections and found that it allowed for early detection and was easy to use.