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Epic Sepsis Model Inpatient Predictive Analytic Tool: A Validation Study.

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This summary is machine-generated.

Implementing the Epic Sepsis Model (ESM) alert system in hospitals reduced sepsis-related mortality by 44%. This electronic health record tool shows promise for improving patient outcomes and decreasing deaths from sepsis.

Keywords:
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Area of Science:

  • Healthcare Informatics
  • Critical Care Medicine
  • Predictive Analytics

Background:

  • Early sepsis treatment is crucial for reducing mortality.
  • The Epic Sepsis Model (ESM) is an electronic medical record tool designed for sepsis prediction.
  • External validation of the ESM's effectiveness is limited.

Purpose of the Study:

  • To evaluate the Epic Sepsis Model (ESM) as a sepsis screening tool.
  • To determine if ESM implementation is associated with reduced sepsis-related mortality.

Main Methods:

  • A before-and-after study design was employed at a 746-bed urban academic level 1 trauma center.
  • Adult acute care inpatients were assessed between January 2018 and July 2019.
  • The ESM system was activated to alert providers for sepsis risk scores >= 5.

Main Results:

  • The ESM demonstrated high sensitivity (86.0%) and negative predictive value (98.11%) as a sepsis screening tool.
  • Following ESM implementation, sepsis-related mortality decreased from 24.3% to 15.9% in alerted patients.
  • Multivariable analysis indicated a significant association between ESM implementation and a 44% reduction in sepsis-related mortality (OR 0.56; 95% CI 0.39-0.80).

Conclusions:

  • The ESM score, used as a screening tool, was associated with a substantial reduction in sepsis-related mortality.
  • Given the widespread use of Epic, the ESM presents a promising strategy for improving sepsis outcomes nationwide.
  • Further research with more rigorous designs is warranted to confirm these findings.