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.

PulseData's ML/AI solution identifies undiagnosed and under-diagnosed patients at risk for chronic conditions and significantly improves HCC accuracy.

PulseData is advancing healthcare with data-driven actionable clinical insights giving payers, providers and other value-based care organizations the power to improve clinical and financial outcomes, close care gaps, and improve HEDIS and CAHPS scores. PulseData leverages large, diverse datasets and deep clinical expertise to effectively identify patients with chronic conditions. Using cutting-edge machine learning and AI models, PulseData enables early intervention, equipping healthcare teams with informed, data-driven insights precisely when they matter most – at the point of care.

PulseData’s thoughtful model development avoids machine learning biases, prioritizes model explainability and ensures optimal model performance. Our tailored collaborative approach with our valued clients creates meaningful, impactful, and relevant workflows. The resulting actionable insights can be viewed on our platform and seamlessly integrated into clinical workflows to enhance and support care management workflows.

At the nexus of technology and healthcare, PulseData empowers providers to make well-informed decisions, which improve patient outcomes, reduce costs, and improve program performance. Learn More at pulsedata.ai.

• 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

PulseData's ML/AI solution identifies undiagnosed and under-diagnosed patients at risk for chronic conditions and significantly improves HCC accuracy.

PulseData's ML/AI solution identifies undiagnosed and under-diagnosed patients at risk for chronic conditions and significantly improves HCC accuracy.