Cerebrum– Our Smart Data and Analytics Engine

• Cerebrum is a reactive intelligent data transformation engine
• Merges the patient data model with external data for actionable decision support
• Provides real-time analysis and machine learning of a patient chart to deliver clinical insights to the provider
• Identify potential interventions
• Patient clustering based on condition configuration

Phix Health is a value-based technology and clinical services partnership that specializes in serving clients that are health risk holders:

• Providers responsible for 30-day readmission rules
• Accountable Care Organizations
• Seriously Ill Patients (Nursing Homes/Assisted Living)
• Payers
• Health Systems / Hospital at Home

Health systems use eCART to quickly and efficiently direct clinical resources toward their most critical patients and ensure timely and consistent care. Our sophisticated reporting and benchmarking further empower clinical leadership to understand and drive practice patterns. eCART draws upon readily available patient data from the EHR, rapidly quantifies disease severity, and predicts likelihood of critical illness onset, hours before it happens. Built upon more than a decade of ongoing scientific research, eCART was developed at the University of Chicago by Dr. Dana Edelson, MD, MS and Dr. Matthew Churpek, MD, PhD and is well chronicled in published literature. The analytic and workflow have been in use in clinical practice since 2016.

At AgileMD, we are building the most advanced real-time predictive analytics and clinical pathways platform for hospitals.

To date, AgileMD tools have been used on nearly 2.5 million patients by more than 80,000 providers in over 150 hospitals, including some of the nation's leading academic medical centers. AgileMD is backed by premier accelerators MATTER, YCombinator, and Rock Health, and our cutting-edge analytics are built on a decade of ongoing research at the University of Chicago. In 2021, AgileMD garnered nearly $3 million in combined federal research and development funding from the National Institutes of Health (NIH) and Health and Human Services (HHS) to further advance our platform.

• Cerebrum engine combines native machine learning capability and complex rulesets to enable reduction of risks in hospitalizations, disease progression and more
• Incorporates Johns Hopkins ACG population health toolkit
• Population centric view allows provider teams to quickly drill down to patients requiring attention and follow up

• 10+ years of published academic literature on value over other early warning scores
• Analytics derived and validated in robust patient datasets 
• Built by clinicians for clinicians, with full cross-team workflow to ensure risk scores are understood and acted upon

• 8+ years in clinical use
• High sensitiviy and specificity, meaning fewer false alarms and more efficient focus on the highest risk patients
• Integrated workflow to ensure that risk scores are not ignored and action is taken
• Robust reporting and benchmarking to drive quality improvement
• Deep EHR-integration