• 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. Additionally, our partners use clinical pathways across ambulatory and inpatient settings to improve care standardization across conditions.

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.

Medical Informatics Corp.’s (MIC) mission is to deliver next-generation technologies to unify patient monitoring workflows for healthcare systems. MIC’s decade of innovation with its clinical platform, Sickbay, integrates over 30,000 vendor-neutral signals on two percent of hospital beds with over 10,000 clinical users in the United States. Most hospital systems lack native resolution data aggregated through a single source, instead deploying a multi-device strategy that silos data and data access time frames. The Sickbay Clinical Platform stands alone as the only FDA-cleared platform to aggregate time-series waveform data across disparate devices at native resolution. Current bedside devices delete data on average after 72 hours, while Sickbay saves the data indefinitely. Sickbay provides a portal through which care providers can review aggregated, time-synchronized data, annotate it, and collaborate to create algorithms (including ML & AI) and evaluate post-event care. Those algorithms and care models can then be reintroduced into the platform to advance care and innovation. Simply put, Sickbay provides the hospital teams their data from anywhere, anytime, to optimize workflows, analysis, and risk stratification across the patient care spectrum. The diverse team at MIC is fundamentally unlocking a blue ocean of new patient monitoring capabilities for ourselves, our partners, and our clients. MIC’s Sickbay saves lives, improves outcomes, streamlines strategy and technologies, and reduces the overall caring cost for hospital patients nationwide.

• 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

The EHR is intended to be a point of care reference to support billing. Traditionally, only documenting discreet vitals from patient monitoring devices at single points.

Sickbay Clinical Platform:

• captures consolidated, persistent, time-series waveform data from networked and non-networked bedside devices at its native resolution
• re-displays near real-time, time aligned signals at an average latency of <25 mSec
• integration of risk scores and analytics

Sickbay is a single, interconnected platform that is designed to support dozens of use cases, therefore competition is dependent upon the use case. In addition to the data agggregation, consolidation, and visualilzation differences referenced under EHR functionality, key differentiators in patient monitoring & virtual care include: 

• vendor neutral device integration
• web-based to support monitoring on any PC, tablet, phone or embedded EHR workflow
• flexible, modular design to enable ability to monitor 50+ patients across units, facilities, and vendors
• unlimited retrospective data, from one second to one year+, to support building and sharing of trends, CDI documentation support, quality reporting
• integration, development and deployment of near real-time risk scores and analytics into established workflows
• automated documentation of vitals, ECG strips, and event trends into the EHR