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Surveillance of Healthcare-Acquired Infections in Queensland, Australia: Data and Lessons From the First 5 Years

Published online by Cambridge University Press:  02 January 2015

Anthony P. Morton ,
Archie C. A. Clements ,
Shane R. Doidge ,
Jenny Stackelroth ,
Merrilyn Curtis  and
Michael Whitby
Anthony P. Morton
Affiliation:
Centre for Healthcare Related Infection Surveillance and Prevention, Queensland Health, Brisbane, Queensland, Australia Infection Management Services, Princess Alexandra Hospital, Brisbane, Queensland, Australia
Archie C. A. Clements*
Affiliation:
Centre for Healthcare Related Infection Surveillance and Prevention, Queensland Health, Brisbane, Queensland, Australia School of Population Health, University of Queensland, Brisbane, Queensland, Australia
Shane R. Doidge
Affiliation:
Centre for Healthcare Related Infection Surveillance and Prevention, Queensland Health, Brisbane, Queensland, Australia
Jenny Stackelroth
Affiliation:
Centre for Healthcare Related Infection Surveillance and Prevention, Queensland Health, Brisbane, Queensland, Australia
Merrilyn Curtis
Affiliation:
Centre for Healthcare Related Infection Surveillance and Prevention, Queensland Health, Brisbane, Queensland, Australia
Michael Whitby
Affiliation:
Centre for Healthcare Related Infection Surveillance and Prevention, Queensland Health, Brisbane, Queensland, Australia Infection Management Services, Princess Alexandra Hospital, Brisbane, Queensland, Australia
*
Centre for Healthcare Related Infection Surveillance and Prevention (CHRISP), Princess Alexandra Hospital, Ipswich Road, Brisbane, Queensland, 4102, Australia ([email protected])
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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.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 29 , Issue 8 , August 2008 , pp. 695 - 701
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2008

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References

1.Weingart, S, Wilson, R, Gibberd, R, Harrison, B. Epidemiology of medical error. BMJ 2000;320:774–777.Google Scholar
2.Berwick, D, Calkins, D, McCannon, C, Hackbarth, A. The 100,000 lives campaign: setting a goal and a deadline for improving health care quality. JAMA 2006;295:324–327.Google Scholar
3.Spelman, D. Hospital-acquired infections. Med J Aust 2002;176:286–291.Google Scholar
4.Bärwolff, S, Sohr, D, Geffers, C, et al.Reduction of surgical site infections after Caesarean delivery using surveillance. J Hosp Infect 2006;64:156–161.Google Scholar
5.Gastmeier, P, Geffers, C, Brandt, C, et al.Effectiveness of a nationwide nosocomial infection surveillance system for reducing nosocomial infections. J Hosp Infect 2006;64:16–22.Google Scholar
6.Geubbels, EL, Nagelkerke, NJ, Mintjes-De Groot, AJ, Vandenbroucke-Grauls, CM, Grobbee, DE, De Boer, AS. Reduced risk of surgical site infections through surveillance in a network. Int J Qual Health Care 2006;18:127–133.Google Scholar
7.Emori, TG, Culver, DH, Horan, TC, et al.National Nosocomial Infections Surveillance System (NNIS): description of surveillance methods. Am J Infect Control 1991;19:19–35.Google Scholar
8.Horan, TC, Gaynes, RP, Martone, WJ, Jarvis, WR, Emori, TG. CDC definitions of nosocomial surgical site infections, 1992: a modification of CDC definitions of surgical wound infections. Infect Control Hosp Epidemiol 1992;13:606–608.Google Scholar
9.Culver, D, Horan, T, Gaynes, R, et al.Surgical wound infection rates by wound class, operative procedure, and patient risk index. Am J Med 1991;91(Suppl 3B):S152–S157.Google Scholar
10.elCAT. Available at: http://www.eICAT.com/. Accessed 18 July 2008.Google Scholar
11.Whitby, M, McLaws, M-L, Collopy, B, et al.Post-discharge surveillance: can patients reliably diagnose surgical wound infections? J Hosp Infect 2002;52:155–160.Google Scholar
12.Ihaka, R, Gentleman, R. R: a language for data analysis and graphics. J Comput Graph Stat 1996;5:299–314.Google Scholar
13.Gillett, S, Solon, R. Hospital utilization and costs study 1998-1990. Vol 1. Canberra: Australian Government Publishing Service, 1991.Google Scholar
14.Hart, M, Lee, K, Hart, R, Robertson, J. Application of attribute control charts to risk adjusted data for monitoring and improving health care performance. Qual Manag Health Care 2003;12:5–19.Google Scholar
15.Christiansen, C, Morris, C. Improving the statistical approach to health care provider profiling. Ann Intern Med 1997;127:764–768.Google Scholar
16.Spiegelhalter, D. Handling over-dispersion of performance indicators. Qual Saf Health Care 2005;14:347–351.Google Scholar
17.Gibberd, R, Parthmeswaran, A, Burtenshaw, K. Using clinical indicators to identify areas for quality improvement. J Qual Clin Pract 2000;20:136–144.Google Scholar
18.OpenBUGS. Available at: http://mathstat.helsinki.fi/openbugs/. Accessed 18 July 2008.Google Scholar
19.Woodworth, G. Biostatistics: a Bayesian introduction. Chapter 11. Hoboken, NJ: Wiley, 2004.Google Scholar
20.Spiegelhalter, D, Abrams, K, Myles, J. Bayesian approaches to clinical trials and health-care evaluation. Chapter 7. Chichester, UK: Wiley, 2004.Google Scholar
21.Carlin, J, Louis, H. 2006. Available at: http://group.monolix.org/documents/ranking-TALouis.ppt. Accessed 18 July 2008.Google Scholar
22.Dreimanis, D, Beckingham, W, Collignon, P, Roberts, J. Staphylococcus aureus bacteraemia surveillance: a relatively easy to collect but accurate clinical indicator on serious health-care associated infections and antibiotic resistance. Aust Infect Control 2005;10:127–130.Google Scholar
23.Collignon, P, Wilkinson, I, Gilbert, G, Grayson, L, Whitby, M. Health care-associated Staphylococcus aureus bloodstream infections: a clinical quality indicator for all hospitals. Med J Aust 2006;184:404–406.Google Scholar
24.Steiner, S, Cook, R, Farewell, V, Treasure, T. Monitoring surgical performance using risk adjusted cumulative sum charts. Biostatistics 2000;1:441–452.Google Scholar
25.Beiles, B, Morton, A. Cumulative sum control charts for assessing performance in arterial surgery. ANZ J Surg 2004;74:146–151.Google Scholar
26.Lovegrove, J, Valencia, O, Treasure, T, Sherlaw-Johnson, C, Gallivan, S. Monitoring the results of cardiac surgery by variable life-adjusted display. Lancet 1997;350:1128–1130.Google Scholar
27.Morton, A. Control charts in hospital epidemiology and infection management: an update. Aust Infect Control 2006;11:6–11.Google Scholar
28.Resnic, F, Zou, K, Do, D, Apostolakis, G, Ohno-Machado, L. Exploration of a Bayesian updating methodology to monitor the safety of interventional cardiovascular procedures. Med Decis Making 2004;24:399–407.Google Scholar
29.Morton, A, Whitby, M, McLaws, M-L, et al.The application of statistical process control charts to the detection and monitoring of hospital-acquired infections. J Qual Clin Pract 2001;21:112–117.Google Scholar
30.McLaws, M-L, Taylor, PC. The Hospital Infection Standardised Surveillance (HISS) programme: analysis of a two-year pilot. J Hosp Infect 2003;53:259–267.CrossRefGoogle ScholarPubMed
31.National Nosocomial Infections Surveillance System. National Nosocomial Infections Surveillance (NISS) System report, data summary from January 1992 through June 2004, issued October 2004. Am J Infect Control 2004;32:470–485.Google Scholar
32.Jodrá, VM, Diaz-Agero Pérez, C, Sainz de los Terreros Soler, L, Saa Requejo, CM, Dacosta Ballesteros, D, Quality Control Indicator Working Group. Results of the Spanish national nosocomial infection surveillance network (VICONOS) for surgery patients from January 1997 through December 2003. Am J Infect Control 2006;34:134–141.Google Scholar
33.Russo, PL, Bull, A, Bennett, RN, et al.The establishment of a statewide surveillance program for hospital-acquired infections in large Victorian public hospitals: a report from the VICNISS coordinating centre. Am J Infect Control 2006;34:430–436.Google Scholar
34.Austin, P, Alter, D, Tu, J. The use of fixed- and random-effects models for classifying hospitals as mortality outliers: a Monte Carlo assessment. Med Decis Making 2003;23:526–539.Google Scholar
35.Clements, ACA, Tong, ENC, Morton, AP, Whitby, M. Risk stratification for surgical site infections in Australia: evaluation of the NNIS risk index. J Hosp Infect 2007;66:148–155.Google Scholar
36.Collignon, P, Nimmo, GR, Gottleib, T, Gosbell, IB. Staphylococcus aureus bacteraemia, Australia. Emerg Infect Dis 2005;11:554–561.CrossRefGoogle ScholarPubMed