Prospective validation of a near real-time EHR-integrated automated SOFA score calculator

Christopher Aakre, Pablo Moreno Franco, Micaela Ferreyra, Jaben Kitson, Man Li, Vitaly D Herasevich

Research output: Contribution to journalArticle

18 Scopus citations

Abstract

Objectives We created an algorithm for automated Sequential Organ Failure Assessment (SOFA) score calculation within the Electronic Health Record (EHR) to facilitate detection of sepsis based on the Third International Consensus Definitions for Sepsis and Septic Shock (SEPSIS-3) clinical definition. We evaluated the accuracy of near real-time and daily automated SOFA score calculation compared with manual score calculation. Methods Automated SOFA scoring computer programs were developed using available EHR data sources and integrated into a critical care focused patient care dashboard at Mayo Clinic in Rochester, Minnesota. We prospectively compared the accuracy of automated versus manual calculation for a sample of patients admitted to the medical intensive care unit at Mayo Clinic Hospitals in Rochester, Minnesota and Jacksonville, Florida. Agreement was calculated with Cohen's kappa statistic. Reason for discrepancy was tabulated during manual review. Results Random spot check comparisons were performed 134 times on 27 unique patients, and daily SOFA score comparisons were performed for 215 patients over a total of 1206 patient days. Agreement between automatically scored and manually scored SOFA components for both random spot checks (696 pairs, κ = 0.89) and daily calculation (5972 pairs, κ = 0.89) was high. The most common discrepancies were in the respiratory component (inaccurate fraction of inspired oxygen retrieval; 200/1206) and creatinine (normal creatinine in patients with no urine output on dialysis; 128/1094). 147 patients were at risk of developing sepsis after intensive care unit admission, 10 later developed sepsis confirmed by chart review. All were identified before onset of sepsis with the ΔSOFA ≥ 2 point criterion and 46 patients were false-positives. Conclusions Near real-time automated SOFA scoring was found to have strong agreement with manual score calculation and may be useful for the detection of sepsis utilizing the new SEPSIS-3 definition.

Original languageEnglish (US)
Pages (from-to)1-6
Number of pages6
JournalInternational Journal of Medical Informatics
Volume103
DOIs
StatePublished - Jul 1 2017

Keywords

  • Automation
  • Clinical decision support
  • Computer-assisted diagnosis
  • Early diagnosis
  • Sepsis

ASJC Scopus subject areas

  • Health Informatics

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