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Validation of Coronary Artery Bypass Graft Surgical Site Infection Surveillance Data From a Statewide Surveillance System in Australia

Published online by Cambridge University Press:  02 January 2015

N. Deborah Friedman ,
Philip L. Russo ,
Ann L. Bull ,
Michael J. Richards  and
Heath Kelly
N. Deborah Friedman*
Affiliation:
Victorian Hospital Acquired Infection Surveillance System Coordinating Centre, Victoria, Australia
Philip L. Russo
Affiliation:
Victorian Hospital Acquired Infection Surveillance System Coordinating Centre, Victoria, Australia
Ann L. Bull
Affiliation:
Victorian Hospital Acquired Infection Surveillance System Coordinating Centre, Victoria, Australia
Michael J. Richards
Affiliation:
Victorian Hospital Acquired Infection Surveillance System Coordinating Centre, Victoria, Australia
Heath Kelly
Affiliation:
Victorian Infectious Diseases Reference Laboratory, Melbourne, Victoria, Australia
*
VICNISS Coordinating Centre, 10 Wreckyn St., North Melbourne, Vic 3605, Australia ([email protected])
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Abstract

Objective.

To measure the accuracy and determine the positive predictive value (PPV) and negative predictive value (NPV) of data submitted to a statewide surveillance system for identifying surgical site infection (SSI) complicating coronary artery bypass graft (CABG) surgery.

Design.

Retrospective review of hospital medical records comparing SSI data with surveillance data submitted by infection control consultants (ICCs).

Setting.

Victorian Hospital Acquired Infection Surveillance System (VICNISS) Coordinating Centre in Victoria, Australia.

Patients.

All patients reported to have an SSI following CABG surgery and a random sample of approximately 10% of patients reported not to have an SSI following CABG surgery.

Results.

The VICNISS ascertainment rate for CABG procedures in Victoria was 95%. One hundred sixty-nine medical records were reviewed, and reviewers agreed with ICCs about 46 (96%) of the patients reported as infected by the ICCs and 31 (91%) of the patients identified with a sternal SSI by the ICCs. In one-third of SSIs, the depth of SSI documented by ICCs was discordant with that documented by the reviewers. Disagreement about patients with donor site SSI was frequent. When the review findings were used as the reference standard, the PPV for ICC-reported SSI was 96% (95% confidence interval [CI], 86%-99%), and the NPV was 97% (95% CI, 92%-99%). For ICC-reported sternal SSI, the PPV was 91% (95% CI, 76%-98%) and the NPV was 98% (95% CI, 94%-100%).

Conclusions.

There was broad agreement on the number of infected patients and the number of patients with sternal SSI. However, discordance was frequent with respect to the depth of sternal SSI and the identification of donor site SSI. We recommend modifications to the methodology for National Noscomial Infection Surveillance System-based surveillance for SSI following CABG surgery.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 28 , Issue 7 , July 2007 , pp. 812 - 817
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2007

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References

1.Gaynes, R, Richards, C, Edwards, J, et al., and the National Nosocomial Surveillance (NNIS) System Hospitals. Feeding back surveillance data to prevent hospital-acquired infections. Emerg Infect Dis 2001;7:295–298.Google Scholar
2.McCoubrey, J, Reilly, J, Mullings, A, Pollock, KG, Johnston, F. Validation of surgical site infection surveillance data in Scotland. J Hosp Infect 2005;61:194–200.CrossRefGoogle ScholarPubMed
3.Haley, RW, Quade, DH, Freemann, HE, the CDC SENIC Planning Committee. Study on the efficacy of nosocomial infection control surveillance (SENIC project): summary of the study Design. Am J Epidemiol 1980;111:472–485.CrossRefGoogle Scholar
4.Glenister, HM, Taylor, LJ, Bartlett, CLR, Cooke, EM, Sedgwick, JA, Mackintosh, CA. An evaluation of surveillance methods for detecting infections in hospital in Patients. J Hosp Infect 1993;23:229–242.Google Scholar
5.Russo, PL, Bull, A, Bennett, NJ, et al.The establishment of a state-wide 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
6.Harrington, G, Russo, P, Spelman, D, et al.Surgical-site infection rates and risk factor analysis in coronary artery bypass graft surgery. Infect Control Hosp Epidemiol 2004;25:472–476.Google Scholar
7.Hook, EB, Regal, RR. Capture-recapture methods in epidemiology: methods and limitations. Epidemiol Rev 1995;17:243–263.CrossRefGoogle ScholarPubMed
8.Broderick, A, Mori, M, Nettleman, MD, Streed, SA, Wenzel, RRNosocomial infections: validation of surveillance and computer modeling to identify patients at risk. Am J Epidemiol 1990;131:734–742.CrossRefGoogle ScholarPubMed
9.Gastmeier, P, Kampf, G, Hauer, T, Schlingmann, J, Schumacher, M, Dasch-ner, F, Ruden, H. Experience with two validation methods in a prevalence survey on nosocomial infections. Infect Control Hosp Epidemiol 1998;19:668–673.Google Scholar
10.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.CrossRefGoogle ScholarPubMed
11.Horan, TC, Emori, TG. Definitions of key terms used in the NNIS System. Am J Infect Control 1997;25:112–116.Google Scholar
12.New classification of physical status. Anesthesiology 1963;24:111.Google Scholar
13.Russo, PL, Bennett, N, Boardman, C, et al.Infections after coronary artery bypass graft surgery in Victorian Hospitals—VICNISS Hospital Acquired Infection Surveillance. Aust N Z J Public Health 2005;29:244–248.Google Scholar
14.Cardo, DM, Falk, PS, Mayhall, G. Validation of surgical wound surveillance. Infect Control Hosp Epidemiol 1993;14:211–215.CrossRefGoogle ScholarPubMed
15.Froggatt, JW, Mayhall, CG. Development and validation of a surveillance program for postoperative wound infections in a university center. In: Program and abstracts of the 89th Annual Meeting of the American Society for Microbiology (New Orleans). 1989.Google Scholar
16.Moore, KL. Clinically Oriented Anatomy. 1st ed. Baltimore: Williams and Wilkins, 1980:12.Google Scholar
17.Roy, MC, Herwaldt, LA, Embrey, R, Kuhns, K, Wenzel, RP, Perl, TM. Does the Centers for Disease Control's NNIS system risk index stratify patients undergoing cardiothoracic operations by their risk of surgical-site infection? Infect Control Hosp Epidemiol 2000;21:186–190.Google Scholar
18.Mangram, AJ, Horan, TC, Pearson, ML, Silver, LC, Jarvis, WR, the Hospital Infection Control Practices Advisory Committee. Guideline for prevention of surgical site infection, 1999. Infect Control Hosp Epidemiol 1999;20:250–280.Google Scholar
19.Wenzel, RP, Osterman, CA, Townsend, TR, et al.Development of a statewide program for surveillance and reporting of hospital-acquired infections. J Infect Dis 1979;140:741–746.Google Scholar
20.Ehrenkranz, NJ, Shultz, JM, Richter, EL. Recorded criteria as a “gold standard” for sensitivity and specificity estimates of surveillance of nosocomial infection: a novel method to measure job performance. Infect Control Hosp Epidemiol 1995;16:697–702.Google Scholar