TY - JOUR
T1 - Variation in identifying sepsis and organ dysfunction using administrative versus electronic clinical data and impact on hospital outcome comparisons
AU - Rhee, Chanu
AU - Jentzsch, Maximilian S.
AU - Kadri, Sameer S.
AU - Seymour, Christopher W.
AU - Angus, Derek C.
AU - Murphy, David J.
AU - Martin, Greg S.
AU - Dantes, Raymund B.
AU - Epstein, Lauren
AU - Fiore, Anthony E.
AU - Jernigan, John A.
AU - Danner, Robert L.
AU - Warren, David K.
AU - Septimus, Edward J.
AU - Hickok, Jason
AU - Poland, Russell E.
AU - Jin, Robert
AU - Fram, David
AU - Schaaf, Richard
AU - Wang, Rui
AU - Klompas, Michael
N1 - Funding Information:
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.
Funding Information:
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).
Publisher Copyright:
© 2020 Royal Society of Chemistry. All rights reserved.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - administrative data
KW - hospital outcomes
KW - organ dysfunction
KW - sepsis
KW - surveillance
UR - http://www.scopus.com/inward/record.url?scp=85058554228&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85058554228&partnerID=8YFLogxK
U2 - 10.1097/CCM.0000000000003554
DO - 10.1097/CCM.0000000000003554
M3 - Article
C2 - 30431493
AN - SCOPUS:85058554228
SN - 0090-3493
VL - 47
SP - 493
EP - 500
JO - Critical Care Medicine
JF - Critical Care Medicine
IS - 4
ER -