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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; 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.
Afiliação
  • Rhee C; Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, MA.
  • Jentzsch MS; Department of Medicine, Brigham and Women's Hospital, Boston, MA.
  • Kadri SS; Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, MA.
  • Seymour CW; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA.
  • Angus DC; Critical Care Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD.
  • Murphy DJ; 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.
  • Martin GS; 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.
  • Dantes RB; Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Emory Critical Care Center, Atlanta, GA.
  • Epstein L; Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Emory Critical Care Center, Atlanta, GA.
  • Fiore AE; Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA.
  • Jernigan JA; Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA.
  • Danner RL; Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA.
  • Warren DK; Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, GA.
  • Septimus EJ; Critical Care Medicine Department, Clinical Center, National Institutes of Health, Bethesda, MD.
  • Hickok J; Department of Medicine, Washington University School of Medicine, St. Louis, MO.
  • Poland RE; Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, MA.
  • Jin R; Texas A&M Health Science Center College of Medicine, Houston, TX.
  • Fram D; Clinical Services Group, HCA Healthcare, Nashville, TN.
  • Schaaf R; Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, MA.
  • Wang R; Clinical Services Group, HCA Healthcare, Nashville, TN.
  • Klompas M; Department of Population Medicine, Harvard Medical School/Harvard Pilgrim Health Care Institute, Boston, MA.
Crit Care Med ; 47(4): 493-500, 2019 04.
Article em En | MEDLINE | ID: mdl-30431493
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sepse / Indicadores de Qualidade em Assistência à Saúde / Registros Eletrônicos de Saúde / Insuficiência de Múltiplos Órgãos País/Região como assunto: America do norte Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sepse / Indicadores de Qualidade em Assistência à Saúde / Registros Eletrônicos de Saúde / Insuficiência de Múltiplos Órgãos País/Região como assunto: America do norte Idioma: En Ano de publicação: 2019 Tipo de documento: Article