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Author Notes:

Chanu Rhee, MD, MPH, Address: Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401, Boston, MA 02215, Phone: 617-509-9987, Fax: 617-859-8112. Email: crhee@bwh.harvard.edu

We thank Richard Platt, MD, MS, Harvard Medical School / Harvard Pilgrim Health Care Institute, and Jonathan B. Perlin, MD, HCA Healthcare, for their support and review of the manuscript.

None of the authors have any conflicts to disclose.

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Research Funding:

This work was supported by the Centers for Disease Control and Prevention (3U54CK000172-05S2) and in part by the Agency for Healthcare Research and Quality (K08HS025008 to C.R.), departmental funds from Harvard Pilgrim Health Care Institute, intramural funds from the National Institutes of Health Clinical Center and National Institute of Allergy and Infectious Diseases, and the National Institutes of Health (R35GM119519 to C.W.S. and D.C.A.). 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, the Agency for Healthcare Research and Quality, or the National Institutes of Health.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Critical Care Medicine
  • General & Internal Medicine
  • administrative data
  • hospital outcomes
  • organ dysfunction
  • sepsis
  • surveillance
  • MORTALITY
  • CARE
  • SCORE
  • DEFINITIONS
  • FAILURE
  • BENCHMARKING
  • TRENDS
  • MODEL

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

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Journal Title:

CRITICAL CARE MEDICINE

Volume:

Volume 47, Number 4

Publisher:

, Pages 493-500

Type of Work:

Article | Post-print: After Peer Review

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.

Copyright information:

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/rdf).
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