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

Rhee C1,2, Jentzsch MS1,3, Kadri SS4, Seymour CW5, Angus DC5, Murphy DJ6, Martin GS6, Dantes RB7, Epstein L7, Fiore AE7, Jernigan JA7, Danner RL4, Warren DK8, Septimus EJ1,9, Hickok J10, Poland RE1,10, Jin R1, Fram D11, Schaaf R11, Wang R1, Klompas M1,2; Centers for Disease Control and Prevention (CDC) Prevention Epicenters Program.

Author information

1: Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, MA.
2: Department of Medicine, Brigham and Women's Hospital, Boston, MA.
3: Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA.
4: Critical Care Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD.
5: The Clinical Research, Investigation and Systems Modeling of Acute illness (CRISMA) Center, Department of Critical Care and Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA.
6: Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Emory Critical Care Center, Atlanta, GA.
7: Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA.
8: Department of Medicine, Washington University School of Medicine, St. Louis, MO.
9: Texas A&M Health Science Center College of Medicine, Houston, TX.
10: Clinical Services Group, HCA Healthcare, Nashville, TN.
11: Commonwealth Informatics, Waltham, MA.

Abstract

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.