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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 research applied machine learning to develop a model predicting surgical cancellations among pediatric patients, and found the feasibility in using these algorithms as a cost-effective quality-improvement measure.
This project will develop and validate new measures needed for automatically identifying violations of the “Five Rights of Medication Safety”: right patient, right dose, right medication, right route, and right frequency.
This study assessed the usability and impact of inpatient portals on patient experience, engagement, and perceptions of care.
This study aimed to improve care transitions for low-income patients with multiple chronic conditions using health information exchange, and found significant reductions in inpatient and emergency department utilization.