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

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.

Factors associated with health care-acquired urinary tract infection.

BACKGROUND: Health care-acquired urinary tract infection is common, and the risk factors should be understood by those who manage hospitalized patients and researchers interested in interventions and programs designed to reduce rates. METHODS: We used multivariable logistic regression to identify factors that demonstrated a statistical association with infection. RESULTS: The incidence rate for infection was 1.66%, and risks increased for patients with prolonged length of stay (odd ratio [OR], 5.28; 95% confidence interval [CI]: 2.46-11.34), urinary catheter (OR, 5.16; 95% CI: 2.84-9.36), unresolved spinal injury (OR, 4.07; 95% CI: 1.04-15.92), transfer to/from another hospital (OR, 2.9; 95% CI: 1.39-6.04), some assistance for daily living prior to admission (OR, 2.58; 95% CI: 1.51-4.41), underlying neurologic disease (OR, 2.59; 95% CI: 1.49-4.49), previous stroke (OR, 1.94; 95% CI: 1.03-3.67), and fracture or dislocation on admission (OR, 3.34; 95% CI: 1.75-6.38). Male sex was protective (OR, 0.44; 95% CI: 0.26-0.77). CONCLUSION: Our data describe a general hospital population and therefore have relevance to many hospital-based health care professionals. The statistical model is a good fit to the data and has good predictive power. We identify high-risk groups and confirm the need for good decision making for managing the risks of health care-acquired urinary tract infection. This requires information on the effectiveness of risk-reducing strategies and the changes to economic costs and health benefits that result and the synthesis of these data in appropriately designed economic models.

Costs of surgical site infections that appear after hospital discharge.

Data were collected from surgical patients in the hospital and on 4 occasions postdischarge. The incidence of postdischarge surgical site infection was 8.46%. Strong evidence showed that these infections caused minor additional costs, which contradicts existing literature. We discuss why previous studies might have overstated costs.