24-Performance Analytics of an Integrated Electronic Health Record Sepsis Trigger Tool
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Sepsis, Administration, 2021
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The Society of Critical Care Medicine's Critical Care Congress features internationally renowned faculty and content sessions highlighting the most up-to-date, evidence-based developments in critical care medicine. This is a presentation from the 2021 Critical Care Congress held virtually from January 31-February 12, 2021.

John Bercier, MD

Introduction/Hypothesis: Machine-learning algorithms in the electronic health record are being used to alert providers of severe sepsis risk. Accurate performance characteristics of these risk scoring tools are necessary to appropriately integrate them into clinical decision making. The Epic® sepsis predictive analytics (SPA) tool relies on clinical variables, patient history and diagnostics to assess risk for severe sepsis. This retrospective chart review evaluated the diagnostic performance of the proprietary Epic® SPA Tool in the emergency department (ED).

Methods: Patients presenting to the ED with at least two of the Systemic Inflammatory Response Syndrome criteria were assessed. All SPA scores were recorded up to 6 hours after triage started. A score >6 was used to indicate a high likelihood of sepsis. The maximum score within the ED encounter or the 6hr window, whichever came first, was used for analysis. Discharge disposition, length of stay (LOS), and discharge diagnosis were recorded. Patients were adjudicated for sepsis by physician committee. The diagnostic performance and receiver operating curves were used to characterize the SPA Tool diagnostic performance. Chi-square and Mann-Whitney U tests were used to analyze non-parametric data.

Results: The SPA scores were obtained for 226 patients of which 188 were evaluated for sepsis and 11.1% were adjudicated as sepsis. The SPA Tool had a 76.2% sensitivity, 86.22% specificity, and a 96.64% NPV based on a cut off score of 6. The AUC was 0.859 (95%CI: 0.77–0.95). Of the 226, patients with a score <6 were more likely to have been discharged from the ED (41.7%) compared to those with a score ≥6 (7.8%, p<0.001) and more likely to have a non-infectious discharge diagnosis (<6: 65.1% v ≥6: 43.1%, p<0.001). 149 patients were admitted to the hospital. Those with a score <6 had a median (IQR) hospital LOS (3 (2,6)) comparable to those with a score ≥6 (4 (2,6), p=0.174). Of the 14 patients admitted to the ICU, there was no difference in the ICU LOS (<6: 3.5(1,6.5) v ≥6: 2.5 (1,6.25) p=0.775).

Conclusions: The benefit of the Epic® SPA tool lies in its negative predictive value when used in a large hospital ED. With limitations of sensitivity, the scoring tool may function best when paired with other high sensitivity diagnostics for optimal patient categorization.


Meta Tag
Content Type Presentation
Knowledge Area Sepsis
Knowledge Area Administration
Knowledge Level Foundational
Knowledge Level Intermediate
Knowledge Level Advanced
Membership Level Select
Tag Scoring Systems
Tag Informatics
Year 2021
performance analytics
sepsis trigger tool
machine learning algorithms
diagnostic performance
infection detection


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