Variation in Identifying Sepsis and Organ Dysfunction Using Administrative Versus Electronic Clinical Data and Impact on Hospital Outcome Comparisons*

Variation in Identifying Sepsis and Organ Dysfunction Using Administrative Versus Electronic Clinical Data and Impact on Hospital Outcome Comparisons*

by Rhee, Chanu; Jentzsch, Maximilian S.; Kadri, Sameer S.; Seymour, Christopher W.; Angus, Derek C.; Murphy, David J.; Martin, Greg S.; Dantes, Raymund B.; Epstein, Lauren; Fiore, Anthony E.; Jernigan, John A.; Danner, Robert L.; Warren, David K.; Septimus, Edward J.; Hickok, Jason; Poland, Russell E.; Jin, Robert; Fram, David; Schaaf, Richard; Wang, Rui; Klompas, Michael; for the Centers for Disease Control and Prevention (CDC) Prevention Epicenters Program  

Critical Care Medicine: April 2019 - Volume 47 - Issue 4 - p 493–500

Objectives: Administrative claims data are commonly used for sepsis surveillance, research, and quality improvement. However, variations in diagnosis, documentation, and coding practices for sepsis and organ dysfunction may confound efforts to estimate sepsis rates, compare outcomes, and perform risk adjustment. We evaluated hospital variation in the sensitivity of claims data relative to clinical data from electronic health records and its impact on outcome comparisons.

Design, Setting, and Patients: Retrospective cohort study of 4.3 million adult encounters at 193 U.S. hospitals in 2013–2014.

Interventions: None.

Measurements and Main Results: Sepsis was defined using electronic health record–derived clinical indicators of presumed infection (blood culture draws and antibiotic administrations) and concurrent organ dysfunction (vasopressors, mechanical ventilation, doubling in creatinine, doubling in bilirubin to ≥ 2.0 mg/dL, decrease in platelets to < 100 cells/µL, or lactate ≥ 2.0 mmol/L). We compared claims for sepsis prevalence and mortality rates between both methods. All estimates were reliability adjusted to account for random variation using hierarchical logistic regression modeling. The sensitivity of hospitals’ claims data was low and variable: median 30% (range, 5–54%) for sepsis, 66% (range, 26–84%) for acute kidney injury, 39% (range, 16–60%) for thrombocytopenia, 36% (range, 29–44%) for hepatic injury, and 66% (range, 29–84%) for shock. Correlation between claims and clinical data was moderate for sepsis prevalence (Pearson coefficient, 0.64) and mortality (0.61). Among hospitals in the lowest sepsis mortality quartile by claims, 46% shifted to higher mortality quartiles using clinical data. Using implicit sepsis criteria based on infection and organ dysfunction codes also yielded major differences versus clinical data.

Conclusions: Variation in the accuracy of claims data for identifying sepsis and organ dysfunction limits their use for comparing hospitals’ sepsis rates and outcomes. Using objective clinical data may facilitate more meaningful hospital comparisons.