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

To date, AgileMD tools have been used on more than 4 million patient encounters by more than 135,000 clinical users in over 250 hospitals, including some of the nation's leading academic medical centers. AgileMD's eCART clinical deterioration prediction software is FDA cleared and the first AI-powered early warning device for ward patients to go through the FDA process with real-world prospective data. 

AgileMD is backed by premier start-up partners MATTER, YCombinator, and Rock Health, and our cutting-edge analytics are built on more than 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 U.S. Department of Health and Human Services (HHS), including the National Institutes of Health (NIH) and the Biomedical Advanced Research and Development Authority (BARDA).

The solution helps health systems to take a step-by-step approach to manage risk from population- to patient-level with easy to use dashboards powered by clinical and claims data. First, it helps understand the current state of risk management in the network with historical comparison to previous years risk scores. Second, it can answer “where to focus” by identifying the cohorts with the least risk recapture rates or maximum dropped/suspect codes, chronic disease distribution, month on month risk capture trend and more. Third, it helps prioritize patients with the largest number of coding gaps and get patient-level risk information to redirect resources strategically that reduces overall risk for the population.

Innovaccer is the data platform that accelerates care innovation through innovative AI technologies. Innovaccer’s AI-powered healthcare platform unifies patient data across systems and care settings, and empowers healthcare organizations with scalable, modern applications that improve clinical, financial, operational, and experiential outcomes. Innovaccer’s EHR-agnostic solutions have been deployed across more than 1,600 hospitals and clinics in the US, enabling care delivery transformation for more than 96,000 clinicians, and helping providers work collaboratively with payers and life sciences companies. Innovaccer has helped its customers unify health records for more than 54 million people and generate over $1.5 billion in cumulative cost savings. The Innovaccer platform is an industry-leading data and analytics platform, the Best in KLAS CRM solution, and the #1 rated population health technology platform by Black Book

• 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

Innovaccer's coder assistant identifies missing codes based on claims data and suggested clinical markers, helping avoid improper data submission and related consequences such as lengthy audits and repayments to CMS. The solution enables physicians and coders to save time by identifying information that could not be directly found in the patient's clinical or claims data. Failing audits, repayments to CMS, and legal ramifications are some of the unfortunate outcomes of improper data submission. Automation helps overcome these challenges by detecting suspect and dropped codes while reducing administrative burden.

Innovaccer’s risk management solutions support these efforts to help healthcare providers achieve their risk goals. The AI-powered coder assistant helps providers address coding challenges by analyzing dropped codes and reviewing claims data over multiple years to identify prospective coding opportunities and surface suspect codes based on evidence. This enables them to receive appropriate reimbursements by providing high-quality care to patients