Category: EHR

Medicasci CDS for Sepsis Risk Prediction Completes Multi-Institutational Usability Study

December 31, 2025 • Miami, Florida INFOTECH Soft has completed multi-institutional usability study of the Medicasci® CDS for Sepsis Risk Prediction pilot. Experienced emergency department and intensive care physicians from three institutions across the United States participated in an evaluation of the Medicasci sepsis risk predictions and user interfaces. Medicasci CDS for Sepsis Risk Prediction usability pilot was deployed as an add-on to OpenEMR and configured with real-world de-ide

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Medicasci CDS for Sepsis Risk Prediction Begins Clinical Pilot at California Hospital

July 1, 2025 • Miami, Florida Medicasci® CDS for Sepsis Risk Prediction has been deployed at a large California healthcare system in the first clinical pilot study of the Medicasci project. About Medicasci CDS for Sepsis Risk Prediction (Pilot) Medicasci® CDS for Sepsis Risk Prediction is a deep learning system for context-sensitive clinical decision support for monitoring and predicting the deterioration of patient health and progression of sepsis risk factors in real-time to impr

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Medicasci CDS for Sepsis Risk Prediction deployed on OpenEMR

October 1, 2024 • Miami, Florida Medicasci® CDS for Sepsis Risk Prediction has been deployed as an add-on to OpenEMR. About Medicasci CDS for Sepsis Risk Prediction (Pilot) Medicasci® CDS for Sepsis Risk Prediction is a deep learning system for context-sensitive clinical decision support for monitoring and predicting the deterioration of patient health and progression of sepsis risk factors in real-time to improve outcomes and optimize the management of care across the hospital pop

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Medicasci CDS for Sepsis Risk Prediction (Pilot) Registered in Epic App Orchard

September 1, 2024 • Miami, Florida Medicasci® CDS for Sepsis Risk Prediction (Pilot) has been registered in Epic System's App Orchard. About Medicasci CDS for Sepsis Risk Prediction (Pilot) Medicasci® CDS for Sepsis Risk Prediction is a deep learning system for context-sensitive clinical decision support for monitoring and predicting the deterioration of patient health and progression of sepsis risk factors in real-time to improve outcomes and optimize the management of care across

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