KenSci AI Platform for Digital Health (Providers)


KenSci AI Platform for Digital Health (Providers)


Power operational, clinical and care workflows with AI-based intelligence

Health providers are looking to do more with their data by activating real-time analytics and AI based predictive insights to improve operational and clinical metrics while delivering better care outcomes.

KenSci's AI Platform for Digital Health is the foundation for all AI initiatives at various stages of a health provider's data modernization journey.

KenSci's AI platform enables health providers with:

Real-time Health Data Pipeline

Managed real-time health data pipeline that transforms data from EMRs and other disparate data sources into industry standard formats, ready for AI and analytics use 

  • Automated real-time AI-optimized data pipeline within your own Azure tenant
  • Repeatable movement of HLS data from EMR, HL7 and other data sources with integration with Microsoft Synapse, Azure Data Factory, FHIR, Microsoft Common Data Model and other familiar applications
  • Data normalized and transformed into health features for BI and AI analytics applications


Kentelligence Mobile App with Real-time KPIs and Dashboards

Mobile app to visualize system-wide real-time KPIs and metrics with a configurable care event alert engine and self-serve analytics portal

  • Real-time Census with system-wide views into ED, COVID-19 Command Center (patient status, bed and ventilator usage), in-patient metrics
  • Configurable care alert engine to provide real-time alerts for key care events
  • Enterprise self-service analytics portal with real-time, retrospective and forecasting dashboards

Prediction Models for Provider Use-cases

Out-of-the-box provider AI "Essential" models with predictive insights for In-Patient scenarios 

  • ED Census: Predict ED volumes for the next 3 days & proactively plan staffing and supplies
  • ED Disposition: Predict if an incoming ED patient will convert to In-patient, observation or discharged
  • Post-Acute Level of Care: Predict post-acute level of care for patient when leaving the hospital
  • Length of Stay (LOS): Predict in-patient length of stay (LOS) for Adults, Pediatric and COVID-19 patients
  • Risk of Readmission (ROR): Predict if patient will return to the hospital within 30 days after discharge