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

Rhee, Chanu MD, MPH1,2; Jentzsch, Maximilian S. MS1,3; Kadri, Sameer S. MD, MS4; Seymour, Christopher W. MD, MSc5; Angus, Derek C. MD, MPH5; Murphy, David J. MD, PhD6; Martin, Greg S. MD, MSc6; Dantes, Raymund B. MD, MPH7; Epstein, Lauren MD, MS7; Fiore, Anthony E. MD, MPH7; Jernigan, John A. MD, MS7; Danner, Robert L. MD4; Warren, David K. MD, MPH8; Septimus, Edward J. MD1,9; Hickok, Jason MBA10; Poland, Russell E. PhD1,10; Jin, Robert MS1; Fram, David BA11; Schaaf, Richard SM11; Wang, Rui PhD1; Klompas, Michael MD, MPH1,2; for the Centers for Disease Control and Prevention (CDC) Prevention Epicenters Program

doi: 10.1097/CCM.0000000000003554
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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.

1Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, MA.

2Department of Medicine, Brigham and Women’s Hospital, Boston, MA.

3Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA.

4Critical Care Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD.

5The 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.

6Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Emory Critical Care Center, Atlanta, GA.

7Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA.

8Department of Medicine, Washington University School of Medicine, St. Louis, MO.

9Texas A&M Health Science Center College of Medicine, Houston, TX.

10Clinical Services Group, HCA Healthcare, Nashville, TN.

11Commonwealth Informatics, Waltham, MA.

*See also p. 599.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://journals.lww.com/ccmjournal).

Supported, in part, by the Centers for Disease Control and Prevention (3U54CK000172-05S2), the Agency for Healthcare Research and Quality (AHRQ) (K08HS025008 to Dr. Rhee), departmental funds from Harvard Pilgrim Health Care Institute, intramural funds from the National Institutes of Health (NIH) Clinical Center and National Institute of Allergy and Infectious Diseases, and the NIH (R35GM119519 to Drs. Seymour and Angus). The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention (CDC), the AHRQ, or the NIH.

Dr. Rhee’s, Mr. Jentzsch’s, and Dr. Klompas’ institutions received funding from CDC. Drs. Rhee’s and Wang’s institution received funding from the AHRQ. Drs. Rhee, Dantes, Fiore, and Septimus received support for article research from the CDC. Drs. Kadri, Seymour, Martin, Danner, and Wang received support for article research from the NIH. Drs. Kadri, Dantes, Epstein, Fiore, Jernigan, Danner, and Septimus disclosed government work. Dr. Martin’s institution received funding from NIH (UL1 TR-002378). Dr. Fiore received support for article research from the U.S. Department for Health and Human Services. Dr. Warren’s institution received funding from Cepheid, and he received funding from Carefusion/Becton, Dickinson and Company (advisory board), Pursuit Vascular (consultant), and Harvard Pilgrim Health (consultant). Dr. Septimus and Mr. Hickok disclosed that Sage Products and Molnlycke contributed antiseptic chlorhexidine product for the Active Bathing to Eliminate Infection (ABATE) trial (unrelated to this article). Clorox, now Medline, contributed products to the Mupirocin-Iodophor ICU Decolonization Swap Out trial (unrelated to this article).

For information regarding this article, E-mail: crhee@bwh.harvard.edu

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