Better sepsis bundle compliance - Better outcomes
NAVOY CDS® is our FDA-cleared solution helping U.S. health systems improve their CMS SEP-1 sepsis bundle compliance through early sepsis detection and tracking patients’ deterioration. The software comes with a powerful suite of tools that empower hospitals looking to boost their quality and safety ratings, and strengthen their bottom line.
Improved sepsis bundle compliance is achieved through timely identification, automated notifications and standardized care protocols.
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.
With NAVOY CDS®, expect a higher clinical and financial yield
Up to 3 h earlier
detection of sepsis
Improved sepsis bundle compliance
Standardized reports for billing and CMS compliance
Sepsis management needs...
Denials can be prevented
Admin cost to
rework a Medicare
Advantage denial
National average sepsis bundle fail rate*
*Apr 1st 2023 – Mar 31st 2024
This standalone demo showcases the core functionality of our solution
AI grounded in healthcare reality
“When the patient is discharged from the ED to the floor, the floor nurse has no knowledge of the sepsis bundle. With NAVOY CDS the floor staff will easily be able to complete ongoing sepsis bundles on time.”
Sepsis Nurse, IL
“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 Coordinator, FL
“Sepsis is the no. 1 condition with the highest rate of claim denials.”
Sepsis Program Coordinator, ID
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- Sjövall F, Persson I. Poster presentation at SCCM Society of Critical Care Medicine, San Francisco, January 21-24 2023.
- 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.
- 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.
- 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.
- 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.