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
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.