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

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

doi:10.1097/ccm.0000000000003554

Cited by 86Sepsis Diagnosis and TreatmentMedical Coding and Health InformationElectronic Health Records Systems

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

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Rhee, Chanu, Jentzsch, Maximilian S., Kadri, Sameer S., Seymour, Christopher W., Angus, Derek C., Murphy, David J., Martin, Greg S., Dantes, Raymund B. +13 more·2019·Critical Care Medicine

DOI 10.1097/ccm.0000000000003554PMC PMC7970408

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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.

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This study used Sepsis-3 clinical criteria to label sepsis cases, an approach that has imperfect concordance with the criterion standard approach of manual physician review.
“First, this study used Sepsis-3 clinical criteria to label sepsis cases, an approach that has imperfect concordance with the criterion standard approach of manual physician review.25,26,27,28”
From Multicenter Prospective Validation of an Updated Proprietary Sepsis Prediction Model (2026) · cites this paper as [27]
The Discussion says the paper’s EHR-based clinical criteria are an imperfect reference standard and that there is no true gold standard for sepsis. But the paper did not review medical records to confirm its criteria (Discussion, limitations), so it does not establish their concordance with manual physician review or describe that review as the criterion standard. The citing study’s own use of Sepsis-3 is not a finding attributed to this source. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Sepsis discharge diagnosis codes are variably applied and miss many patients initially treated for sepsis but ultimately diagnosed with other conditions.
“We did not use sepsis discharge diagnosis codes because these are variably applied and miss many patients initially treated for sepsis but ultimately diagnosed with other conditions.”
From Trends in empiric broad-Spectrum antibiotic use for suspected community-onset Sepsis in US hospitals (2024) · cites this paper as [24]

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1659. Variation in Identifying Sepsis and Organ Dysfunction Using Administrative Versus Clinical Data and Impact on Hospital Outcome Comparisons
Rhee, C., Jentzsch, M. S., Kadri, S. S., Seymour, C. W., Angus, D. C., Murphy, D. J., Martin, G. S., Dantes, R., Epstein, L. H., Fiore, A. E., et al. (2018) · Open Forum Infectious Diseases · doi:10.1093/ofid/ofy209.119 · Cited by 1 · see citing works
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Authors: Rhee, C., Jentzsch, M. S., Kadri, S. S., Seymour, C. W., Angus, D. C., Murphy, D. J., Martin, G. S., Dantes, R. B., Epstein, L., Fiore, A. E., Jernigan, J. A., Danner, R. L., Warren, D. K., Septimus, E. J., Hickok, J., Poland, R. E., Jin, R., Fram, D., Schaaf, R., Wang, R., & Klompas, M.
Affiliations: Brigham and Women's Hospital (US)
Harvard University (US)
National Institutes of Health (US)
University of Pittsburgh (US)
Emory University (US)
Centers for Disease Control and Prevention (US)
Washington University in St. Louis (US)
Texas A&M Health Science Center (US)
ORCID: Rhee, Chanu
Kadri, Sameer S.
Seymour, Christopher W.
Angus, Derek C.
Murphy, David J.
Martin, Greg S.
Dantes, Raymund B.
Epstein, Lauren
Jernigan, John A.
Danner, Robert L.
Warren, David K.
Septimus, Edward J.
Wang, Rui
Klompas, Michael
Venue: Critical Care Medicine
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2019-04
Volume: 47
Issue: 4
Pages: 493-500
ISSN: 0090-3493 (ISSN-L)
DOI: 10.1097/ccm.0000000000003554
PMC: PMC7970408
OpenAlex: W2901221479
Cited by: 85
References: 40
Citations by year: 2026: 18 · 2025: 14 · 2024: 6 · 2023: 9 · 2022: 7 · 2021: 8 · 2020: 13 · 2019: 9 · 2018: 1
FWCI: 6.05
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Critical Care Medicine (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: Centers for Disease Control and Prevention (U54CK000172)
Agency for Healthcare Research and Quality (K08HS025008)
National Institute of General Medical Sciences (R35GM119519)
Topics: Health Sciences › Medicine › Epidemiology › Sepsis Diagnosis and Treatment
Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
Keywords: sepsis, organ dysfunction, administrative claims data, electronic health records, sepsis surveillance, risk adjustment, sepsis mortality, acute kidney injury, thrombocytopenia, liver injury, shock, diagnostic sensitivity, ICD-10 coding
MeSH terms: Adult, Female, Humans, Male, Middle Aged, Multiple Organ Failure, Retrospective Studies, United States, Hospital Mortality, Sepsis, Quality Indicators, Health Care, Electronic Health Records

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

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