An artificial intelligence-powered learning health system to improve sepsis detection and quality of care: a before-and-after study - Takeaways - MDSpire

An artificial intelligence-powered learning health system to improve sepsis detection and quality of care: a before-and-after study

  • By

  • Jérémie Despraz

  • Raphaël Matusiak

  • Snežana Nektarijevic

  • Valerio Rossetti

  • François Bastardot

  • Rachid Akrour

  • Andreas Konasch

  • Emeline Gauthiez

  • Olivier Pignolet

  • Santino Pepe

  • Jean-Daniel Chiche

  • Daniel E. Kaufmann

  • Thierry Calandra

  • Jean Louis Raisaro

  • Sylvain Meylan

  • January 20, 2026

  • 0 min

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  • 1

    Sepsis affects 50 million people and causes 11 million deaths annually, highlighting the need for improved detection and management strategies.

  • 2

    The Surviving Sepsis Campaign emphasizes timely antibiotics and fluid resuscitation, yet adherence to guidelines is often suboptimal.

  • 3

    The Sepsis Learning Health System (SLHS) integrates AI-driven monitoring with a clinical pathway to enhance sepsis detection and care quality.

  • 4

    HERACLES, a machine learning algorithm, predicts sepsis probabilities and generates actionable care indicators for clinical teams.

  • 5

    The SLHS registry included 97,559 hospital stays by December 2024, demonstrating its extensive implementation across multiple wards.

Original Source(s)

An artificial intelligence-powered learning health system to improve sepsis detection and quality of care: a before-and-after study

  • by Jérémie Despraz, Raphaël Matusiak, Snežana Nektarijevic, Valerio Rossetti, François Bastardot, Rachid Akrour, Andreas Konasch, Emeline Gauthiez, Olivier Pignolet, Santino Pepe, Jean-Daniel Chiche, Daniel E. Kaufmann, Thierry Calandra, Jean Louis Raisaro, Sylvain Meylan

  • January 20, 2026

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