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A Data-Driven Approach to Quantifying Immune States in Sepsis
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Alert to Action: Implementing Artificial Intelligence-Driven Clinical Decision Support Tools for Sepsis.

Alexander Fixler1, Blake Oliaro1, Marshall Frieden2

  • 1The University of Queensland Medical School, Ochsner Clinical School, New Orleans, LA.

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|September 15, 2023
PubMed
Summary
This summary is machine-generated.

New clinical decision support tools improve sepsis detection and management. These tools, integrated into electronic health records, show higher user interaction and better alert-to-action ratios for sepsis care.

Keywords:
Artificial intelligencedecision support system–clinicalsepsis

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Area of Science:

  • Medical Informatics
  • Critical Care Medicine
  • Health Services Research

Background:

  • Sepsis is a leading cause of in-hospital mortality.
  • International initiatives like Surviving Sepsis Campaign aim to reduce sepsis-related deaths.
  • Effective sepsis management requires timely detection and intervention.

Purpose of the Study:

  • To evaluate a novel suite of integrated clinical decision support (CDS) tools for sepsis detection and management.
  • To assess the usability and effectiveness of CDS tools driven by a predictive learning algorithm.
  • To improve patient outcomes through enhanced sepsis multidisciplinary care.

Main Methods:

  • Implementation of a novel suite of integrated CDS tools within the electronic health record.
  • Utilizing a predictive learning algorithm to drive CDS functionalities.
  • Applying industry-standard heuristics for interface design to enhance usability.

Main Results:

  • The novel CDS tools demonstrated a significantly higher alert-to-action ratio (16.46%) compared to existing best practice alerts (8.4% to 12.1%).
  • Intuitive design strategies encouraged higher user interaction and completion of best practice alerts.
  • Team-wide visualization of clinical decisions via a checklist facilitated collaborative care.

Conclusions:

  • The developed CDS tools represent an improvement over legacy systems for sepsis detection and management.
  • Intuitive design and team-based visualization are key factors in enhancing the effectiveness of CDS tools.
  • The pilot results suggest potential broader applications of these CDS tools beyond sepsis alerting.