Attributable Length of Stay, Mortality Risk, and Costs of Bacterial Health Care-Associated Infections in Australia: A Retrospective Case-cohort Study

X J Lee; A J Stewardson; L J Worth; N Graves; T M Wozniak

doi:10.1093/cid/ciaa1228

Attributable Length of Stay, Mortality Risk, and Costs of Bacterial Health Care-Associated Infections in Australia: A Retrospective Case-cohort Study

Clin Infect Dis. 2021 May 18;72(10):e506-e514. doi: 10.1093/cid/ciaa1228.

Authors

X J Lee¹, A J Stewardson^{2

3}, L J Worth^{4

5}, N Graves⁶, T M Wozniak⁷

Affiliations

¹ Australian Centre for Health Services Innovation, Queensland University of Technology, Queensland, Australia.
² Department of Infectious Diseases, The Alfred and Central Clinical School.
³ Monash University, Victoria, Australia.
⁴ Victorian Healthcare Associated Infection Surveillance System Coordinating Centre, Doherty Institute, Victoria, Australia.
⁵ National Centre for Infections in Cancer, Sir Peter MacCallum Department of Medicine, University of Melbourne, Victoria, Australia.
⁶ Duke University and the National University of Singapore Medical School, Singapore.
⁷ Charles Darwin University, Menzies School of Health Research, Global & Tropical Health Division, Northern Territory, Australia.

Abstract

Background: Unbiased estimates of the health and economic impacts of health care-associated infections (HAIs) are scarce and focus largely on patients with bloodstream infections (BSIs). We sought to estimate the hospital length of stay (LOS), mortality rate, and costs of HAIs and the differential effects on patients with an antimicrobial-resistant infection.

Methods: We conducted a multisite, retrospective case-cohort of all acute-care hospital admissions with a positive culture of 1 of the 5 organisms of interest (Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, or Enterococcus faecium) from 1 January 2012 through 30 December 2016. Data linkage was used to generate a data set of statewide hospital admissions and pathology data. Patients with bloodstream, urinary, or respiratory tract infections were included in the analysis and matched to a sample of uninfected patients. We used multistate survival models to generate LOS, and logistic regression to derive mortality estimates.

Results: We matched 20 390 cases to 75 635 uninfected control patients. The overall incidence of infections due to the 5 studied organisms was 116.9 cases per 100 000 patient days, with E. coli urinary tract infections (UTIs) contributing the largest proportion (51 cases per 100 000 patient days). The impact of a UTI on LOS was moderate across the 5 studied pathogens. Resistance significantly increased LOS for patients with third-generation cephalosporin-resistant K. pneumoniae BSIs (extra 4.6 days) and methicillin-resistant S. aureus BSIs (extra 2.9 days). Consequently, the health-care costs of these infections were higher, compared to corresponding drug-sensitive strains.

Conclusions: The health burden remains highest for BSIs; however, UTIs and respiratory tract infections contributed most to the health-care system expenditure.

Keywords: antimicrobial resistance; cost; hospital-associated infections; length of stay; mortality.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Anti-Bacterial Agents / therapeutic use
Australia / epidemiology
Bacteremia* / drug therapy
Bacteremia* / epidemiology
Cohort Studies
Cross Infection* / drug therapy
Cross Infection* / epidemiology
Delivery of Health Care
Escherichia coli
Humans
Length of Stay
Methicillin-Resistant Staphylococcus aureus*
Retrospective Studies

Substances

Anti-Bacterial Agents