• eCART is a research-based, AI-driven software as a medical device (SaMD) that utilizes a machine learning algorithm to continuously assess hospitalized patients’ risk of impending death or intensive care unit (ICU) transfer, assisting medical staff in swift and accurate recognition of patients requiring increased medical attention. 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.
• eCART received FDA 510(k) clearance in 2024, with clinical performance data of nearly two million hospitalizations from 21 hospitals, including an unprecedented level of real-world prospective data, to ensure consistent accuracy across geography, age, race, and top medical conditions (e.g. sepsis, COPD, heart failure). 
• Built upon more than a decade of ongoing scientific research, eCART was developed at UChicago Medicine 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, our mission is to improve patient outcomes by making evidence-based care universally accessible. We deliver this through intelligent clinical triggers, deeply integrated workflows, and actionable measurement that empowers clinicians at the point of care.

Founded at the University of Chicago more than 14 years ago, AgileMD solutions now support over 140,000 providers across 400+ U.S. hospitals, informing care for nearly 4.5 million patient encounters. Our impact has been validated in 90+ peer-reviewed publications, demonstrating meaningful improvements in care standardization, mortality, length of stay, and cost management.

AgileMD’s eCART all-cause early warning software is FDA-cleared and proven to outperform sepsis-specific scores. With embedded clinical pathways, it helps frontline teams identify risk earlier and follow role-specific guidelines to order, document, and escalate care.

AgileMD has been awarded nearly $3 million in federal funding from the U.S. Department of Health & Human Services (HHS), underscoring our commitment to advancing high-quality, data-driven clinical care.

1. First-of-Its-Kind 6-in-1 Smart Infant Hub: Combines an infant scale, changing pad, temperature sensor, growth tracker, milestone monitor, and AI health assistant which streamlines multiple nursery tools into one sleek, connected device.
2. Clinically Aligned Weight Monitoring at Home: Enables NICUs, pediatricians, and care teams to monitor infant growth post-discharge, reducing the risk of readmissions due to poor weight gain or feeding issues.
3. AI-Powered Parent Coaching: Delivers real-time answers to common questions, milestone alerts, and feeding guidance, easing anxiety and empowering caregivers with on-demand support.
4. Seamless Data Sharing with Providers: Offers bi-directional integration potential with EHRs, enabling early detection of issues and remote monitoring aligned with value-based care models.
5. Designed for Equity & Accessibility: Inclusive design supports diverse caregiver needs, including health literacy friendly language and culturally relevant education and reminders.
6. Replaces Multiple Nursery Tools: Eliminates the need for separate scales, pads, trackers, and apps, simplifying the caregiver experience while increasing compliance with post-discharge care plans.
7. Supports Health System Metrics: Improves newborn care transitions, supports HEDIS and Medicaid quality measures, and contributes to lower avoidable readmissions and better long-term outcomes.

• Continuously monitors EHR data in real time
• Stratifies hospitalized patients by risk of impending all-cause clinical deterioration and sepsis
• Notifies inpatient providers when patient may need additional assessment and management
• Recommends clinical pathways with integrated order entry

• Authorized: FDA 510(k) cleared
• Tested: Derived and validated in nearly 3 million patient encounters across 28 hospitals
• Experienced: 8+ years in clinical use; 10+ years of published academic literature on value over other early warning scores
• Accurate: High sensitiviy and specificity, meaning fewer false alarms and more efficient focus on the highest risk patients
• Integrated: Embedded cross-team workflow ensures that risk scores are not ignored and action is taken
• Benchmarked: Robust reporting, benchmarking, and implementation support drive quality improvement