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Effect of Healthcare-Acquired Infection on Length of Hospital Stay and Cost

Published online by Cambridge University Press:  02 January 2015

Nicholas Graves ,
Diana Weinhold ,
Edward Tong ,
Frances Birrell ,
Shane Doidge ,
Prabha Ramritu ,
Kate Halton ,
David Lairson  and
Michael Whitby
Nicholas Graves*
Affiliation:
Centre for Healthcare Related Infection Surveillance and Prevention, Princess Alexandra Hospital, Brisbane, Australia Institute of Biomedical and Health Innovation, School of Public Health, Queensland University of Technology, Brisbane, Australia
Diana Weinhold
Affiliation:
London School of Economics, London, United Kingdom
Edward Tong
Affiliation:
Centre for Healthcare Related Infection Surveillance and Prevention, Princess Alexandra Hospital, Brisbane, Australia
Frances Birrell
Affiliation:
Centre for Healthcare Related Infection Surveillance and Prevention, Princess Alexandra Hospital, Brisbane, Australia
Shane Doidge
Affiliation:
Centre for Healthcare Related Infection Surveillance and Prevention, Princess Alexandra Hospital, Brisbane, Australia
Prabha Ramritu
Affiliation:
Centre for Healthcare Related Infection Surveillance and Prevention, Princess Alexandra Hospital, Brisbane, Australia
Kate Halton
Affiliation:
Centre for Healthcare Related Infection Surveillance and Prevention, Princess Alexandra Hospital, Brisbane, Australia Institute of Biomedical and Health Innovation, School of Public Health, Queensland University of Technology, Brisbane, Australia
David Lairson
Affiliation:
School of Public Health, University of Texas Health Science Center at Houston, Houston
Michael Whitby
Affiliation:
Centre for Healthcare Related Infection Surveillance and Prevention, Princess Alexandra Hospital, Brisbane, Australia
*
School of Public Health, Queensland University of Technology, Victoria Park Rd., Kelvin Grove, QLD 4059, Australia (n.graves@qut.edu.au)
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Abstract

Objective.

To estimate the independent effect of a single lower respiratory tract infection, urinary tract infection, or other healthcare-acquired infection on length-of-stay and variable costs and to demonstrate the bias from omitted variables that is present in previous estimates.

Design.

Prospective cohort study.

Setting.

A tertiary care referral hospital and regional district hospital in southeast Queensland, Australia.

Patients.

Adults aged 18 years or older with a minimum inpatient stay of 1 night who were admitted to selected clinical specialities.

Results.

Urinary tract infection was not associated with an increase in length of hospital stay or variable costs. Lower respiratory tract infection was associated with an increase of 2.58 days in the hospital and variable costs of AU$24, whereas other types of infection were associated with an increased length of stay of 2.61 days but not with variable costs. Many other factors were found to be associated with increased length of stay and variable costs alongside healthcare-acquired infection. The exclusion of these variables caused a positive bias in the estimates of the costs of healthcare-acquired infection.

Conclusions.

The existing literature may overstate the costs of healthcare-acquired infection because of bias, and the existing estimates of excess costs may not make intuitive sense to clinicians and policy makers. Accurate estimates of the costs of healthcare-acquired infection should be made and used in appropriately designed decision-analytic economic models (ie, cost-effectiveness models) that will make valid and believable predictions of the economic value of increased infection control.

Information

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 28 , Issue 3 , March 2007 , pp. 280 - 292
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2007

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