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Infect Control Hosp Epidemiol. 2008 Aug;29(8):695-701. doi: 10.1086/589904.

Surveillance of healthcare-acquired infections in Queensland, Australia: data and lessons from the first 5 years.

Author information

1
Centre for Healthcare Related Infection Surveillance and Prevention, Queensland Health, Brisbane, Queensland, Australia.

Abstract

OBJECTIVE:

To present healthcare-acquired infection surveillance data for 2001-2005 in Queensland, Australia.

DESIGN:

Observational prospective cohort study.

SETTING:

Twenty-three public hospitals in Queensland.

METHODS:

We used computer-assisted surveillance to identify episodes of surgical site infection (SSI) in surgical patients. The risk-adjusted incidence of SSI was calculated by means of a risk-adjustment score modified from that of the US National Nosocomial Infections Surveillance System, and the incidence of inpatient bloodstream infection (BSI) was adjusted for risk on the basis of hospital level (level 1, tertiary referral center; level 2, large general hospital; level 3, small general hospital). Funnel and Bayesian shrinkage plots were used for between-hospital comparisons.

PATIENTS:

A total of 49,804 surgical patients and 4,663 patients who experienced healthcare-associated BSI.

RESULTS:

The overall cumulative incidence of in-hospital SSI ranged from 0.28% (95% confidence interval [CI], 0%-1.54%) for radical mastectomies to 6.15% (95% CI, 3.22%-10.50%) for femoropopliteal bypass procedures. The incidence of inpatient BSI was 0.80, 0.28, and 0.22 episodes per 1,000 occupied bed-days in level 1, 2, and 3 hospitals, respectively. Staphylococcus aureus was the most commonly isolated microorganism for SSI and BSI. Funnel and shrinkage plots showed at least 1 hospital with a signal indicating a possible higher-than-expected rate of S. aureus-associated BSI.

CONCLUSIONS:

Comparisons between hospitals should be viewed with caution because of imperfect risk adjustment. It is our view that the data should be used to improve healthcare-acquired infection control practices using evidence-based systems rather than to judge institutions.

PMID:
18690786
DOI:
10.1086/589904
[Indexed for MEDLINE]

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