Better sepsis bundle compliance - Better outcomes

Precision-Driven Sepsis Care

NAVOY CDS® is based on our FDA-cleared solution supporting health systems improve their CMS SEP-1 sepsis bundle compliance through early sepsis detection and tracking patients’ deterioration. Our solution integrates in your EHR, and comes with a powerful suite of tools to boost hospitals’ quality and safety ratings, and strengthen their bottom line.

Bundle Steward™ serves as the compliance backbone of our solution. It automates, tracks, and reinforces every component of the SEP‑1 sepsis bundle, ensuring timely execution and accurate documentation of interventions. By simplifying compliance reporting, supporting clinical workflows and reducing revenue loss, it helps hospitals deliver better care while meeting regulatory requirements.

NAVOY CDS® leverages routine clinical parameters through real-time EHR integration, empowering providers to improve sepsis management from ED triage through the entire patient journey.

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Impactful Results With NAVOY CDS®

Data-driven precision medicine that leverages advanced analytics and clinical insights to enhance patient outcomes, optimize treatment decisions, and improve financial performance across healthcare systems.

%

Fewer sepsis cases

%

Fewer insurance denials

%

Fewer sepsis bundle fails

Return per 100k ED visits

How NAVOY CDS® Enhances Sepsis Management

Real-Time Sepsis Detection

Utilizes advanced algorithms to identify sepsis up to 3 hours earlier, enhancing patient care and outcomes.

Automated Notifications

Ensures timely alerts to healthcare teams, facilitating prompt intervention and adherence to sepsis protocols.

Standardized Care Protocols

Streamlines the implementation of consistent treatment guidelines, reducing variability and improving compliance.

What is the SEP-1 measure and why is it important?

SEP-1, CMS’s Severe Sepsis and Septic Shock Management Bundle, is the time-sensitive measure requiring hospitals to complete specific interventions within three and six hours of sepsis recognition. Compliance impacts reimbursement and public reporting, making streamlined protocols, EHR alerts, teamwork, and thorough documentation essential to ensure timely care, avoid financial penalties, and improve patient outcomes.

How does SEP-1 affect value-based payment models?

CMS has incorporated SEP-1 into the Hospital Value-Based Purchasing Program, linking sepsis care performance directly to financial reimbursement. All-or-none compliance with the 3- and 6-hour bundle now affects a hospital’s Total Performance Score, with high compliance earning incentives and poor performance risking penalties, making SEP-1 a high-stakes measure requiring executive focus, resources, technology, and thorough documentation.

How does NAVOY CDS® support SEP-1 compliance?

AlgoDx’s NAVOY CDS® supports hospital compliance with CMS’s SEP-1 bundle by enhancing early sepsis detection and documentation. Fully integrated with the EHR, it provides AI-driven alerts, automated notifications, and standardized checklists to facilitate timely completion of 3- and 6-hour bundle tasks, streamlining workflows, ensuring precise time-stamping, and improving both clinical and financial outcomes.

AI Grounded In Healthcare Reality

“The sepsis coordinator’s work is heavily manual. Their goal is to do chart review right after discharge, but very often they’re short of staff and can’t keep up.”
Sepsis Nurse, IL

“Sepsis ranks as the leading condition associated with the highest rate of claim denials.“
Sepsis Program Coordinator, ID

Standalone Demo Showcasing Core Functionality

Supported By Peer-Reviewed Publications

Clinical Validation Trial:

 

  1. Persson I, Macura A, Becedas D, Sjövall F. Early prediction of sepsis in intensive care patients using the machine learning algorithm NAVOY® Sepsis, a prospective randomized clinical validation study. J Crit Care. 2024 Apr;80:154400. doi: 10.1016/j.jcrc.2023.154400.
  2. Sjövall F, Persson I. Poster presentation at SCCM Society of Critical Care Medicine, San Francisco, January 21-24 2023.

Health Economic Publications:

  1. Hjelmgren J, Schmidt M, Geahchan C, Becedas D, Hidou C. Poster presentation: ISPOR–The Professional Society for Health Economics and Outcomes Research, November 2022, Boston, MA.
  2. Ericson O, Hjelmgren J, Sjövall F, Söderberg J, Persson I. The Potential Cost and Cost-Effectiveness Impact of Using a Machine Learning Algorithm for Early Detection of Sepsis in Intensive Care Units in Sweden. JHEOR. 2022;9(1):101-110. doi:10.36469/jheor.2022.33951.
  1. Persson I, Östling A, Arlbrandt M, Söderberg J, Becedas D. A Machine Learning Sepsis Prediction Algorithm for Intended Intensive Care Unit Use (NAVOY Sepsis): Proof-of-Concept Study. JMIR Form Res 2021;5(9):e28000. DOI: 10.2196/28000.