Cited by 664

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Epidemiology and Costs of Sepsis in the United States—An Analysis Based on Timing of Diagnosis and Severity Level*

Paoli, Carly J., Reynolds, Mark A., Sinha, Meenal, Gitlin, Matthew, Crouser, Elliott·2018·Critical Care Medicine

Abstract

Objectives: To characterize the current burden, outcomes, and costs of managing sepsis patients in U.S. hospitals. Design: A retrospective observational study was conducted using the Premier Healthcare Database, which represents ~20% of U.S. inpatient discharges among private and academic hospitals. Hospital costs were obtained from billing records per the cost accounting method used by each hospital. Descriptive statistics were performed on patient demographics, characteristics, and clinical and economic outcomes for the index hospitalization and 30-day readmissions. Setting: Sepsis patient hospitalizations, including inpatient, general ward, and ICU (intermediate and/or step-down). Patients: Adults over 18 years old with a hospital discharge diagnosis code of sepsis from January 1, 2010, to September 30, 2016. Interventions: None. This was a retrospective observational study of deidentified data. Measurements and Main Results: The final study cohort consisted of 2,566,689 sepsis cases, representing patients with a mean age of 65 years (50.8% female). Overall mortality was 12.5% but varied greatly by severity (5.6%, 14.9%, and 34.2%) for sepsis without organ dysfunction, severe sepsis, and septic shock, respectively. Costs followed a similar pattern increasing by severity level: $16,324, $24,638, and $38,298 and varied widely by sepsis present at admission ($18,023) and not present at admission ($51,022). Conclusions: The highest burden of incidence and total costs occurred in the lowest severity sepsis cohort population. Sepsis cases not diagnosed until after admission, and those with increasing severity had a higher economic burden and mortality on a case-by-case basis. Methods to improve early identification of sepsis may provide opportunities for reducing the severity and economic burden of sepsis in the United States.

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  • The next most common sepsis comorbidities are diabetes mellitus, hypertension, cardiovascular disease and stroke, obesity, chronic kidney disease and chronic obstructive pulmonary disease.

    “The next most common comorbidities are highly networked conditions strongly associated with social stress and economic marginalization including diabetes mellitus, hypertension, cardiovascular disease (CVD) and stroke, obesity, chronic kidney disease and chronic obstructive pulmonary disease (COPD)”

    From On race, human variation, and who gets and dies of sepsis (2022) · cites this paper as Paoli et al., 2018

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Research works printed but not linked: 16

  1. Angus, 2001, Epidemiology of severe sepsis in the United States: Analysis of incidence, outcome, and associated costs of care., Crit Care Med, 29, 1303, 10.1097/00003246-200107000-00002 · DOI · Paper page
  2. Liu, 2014, Hospital deaths in patients with sepsis from 2 independent cohorts., JAMA, 312, 90, 10.1001/jama.2014.5804 · DOI
  3. Martin, 2012, Sepsis, severe sepsis and septic shock: Changes in incidence, pathogens and outcomes., Expert Rev Anti Infect Ther, 10, 701, 10.1586/eri.12.50 · DOI
  4. Judd, 2014, Clinical and economic impact of a quality improvement initiative to enhance early recognition and treatment of sepsis., Ann Pharmacother, 48, 1269, 10.1177/1060028014541792 · DOI · Paper page
  5. Whiles, 2017, Increased time to initial antimicrobial administration is associated with progression to septic shock in severe sepsis patients., Crit Care Med, 45, 623, 10.1097/CCM.0000000000002262 · DOI
  6. Ferrer, 2014, Empiric antibiotic treatment reduces mortality in severe sepsis and septic shock from the first hour: Results from a guideline-based performance improvement program., Crit Care Med, 42, 1749, 10.1097/CCM.0000000000000330 · DOI
  7. Filbin, 2014, Sepsis visits and antibiotic utilization in U.S. emergency departments*., Crit Care Med, 42, 528, 10.1097/CCM.0000000000000037 · DOI
  8. Liu, 2017, The timing of early antibiotics and hospital mortality in sepsis., Am J Respir Crit Care Med, 196, 856, 10.1164/rccm.201609-1848OC · DOI · Paper page
  9. Pruinelli, 2018, Delay within the 3-hour surviving sepsis campaign guideline on mortality for patients with severe sepsis and septic shock., Crit Care Med, 46, 500, 10.1097/CCM.0000000000002949 · DOI
  10. Jones, 2016, Outcomes and resource use of sepsis-associated stays by presence on admission, severity, and hospital type., Med Care, 54, 303, 10.1097/MLR.0000000000000481 · DOI
  11. Singer, 2016, The third international consensus definitions for sepsis and septic shock (Sepsis-3)., JAMA, 315, 801, 10.1001/jama.2016.0287 · DOI · Paper page
  12. Ost, 2003, Decision analysis of antibiotic and diagnostic strategies in ventilator-associated pneumonia., Am J Respir Crit Care Med, 168, 1060, 10.1164/rccm.200302-199OC · DOI
  13. Houck, 2004, Timing of antibiotic administration and outcomes for Medicare patients hospitalized with community-acquired pneumonia., Arch Intern Med, 164, 637, 10.1001/archinte.164.6.637 · DOI
  14. Prescott, 2014, Increased 1-year healthcare use in survivors of severe sepsis., Am J Respir Crit Care Med, 190, 62, 10.1164/rccm.201403-0471OC · DOI
  15. Rhee, 2017, Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009-2014., JAMA, 318, 1241, 10.1001/jama.2017.13836 · DOI · Paper page
  16. Jafarzadeh, 2016, Quantifying the improvement in sepsis diagnosis, documentation, and coding: The marginal causal effect of year of hospitalization on sepsis diagnosis., Ann Epidemiol, 26, 66, 10.1016/j.annepidem.2015.10.008 · DOI

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Metadata

Authors
Paoli, C. J., Reynolds, M. A., Sinha, M., Gitlin, M., & Crouser, E.
Affiliations
  • Health Economics and Reimbursement, Beckman Coulter, Inc., Brea, CA.
  • Premier Applied Sciences, Premier, Inc., Charlotte, NC.
  • Health Economics and Outcomes Research, BluePath Solutions, Los Angeles, CA.
  • Critical Care Medicine, Ohio State University Wexner Medical Center, Columbus, OH.
Venue
Critical Care Medicine
Published
2018-12
Volume
46
Issue
12
Pages
1889-1897
ISSN
0090-3493
Cited by
664
References
2
Language
en

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