Hostname: page-component-76fb5796d-r6qrq Total loading time: 0 Render date: 2024-04-26T23:18:13.368Z Has data issue: false hasContentIssue false
  • English
  • Français

Validation of a Modified Version of the National Nosocomial Infections Surveillance System Risk Index for Health Services Research

Published online by Cambridge University Press:  02 January 2015

Nick Daneman ,
Andrew E. Simor  and
Donald A. Redelmeier
Nick Daneman*
Affiliation:
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada University of Toronto, Toronto, Ontario, Canada
Andrew E. Simor
Affiliation:
Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada University of Toronto, Toronto, Ontario, Canada
Donald A. Redelmeier
Affiliation:
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada University of Toronto, Toronto, Ontario, Canada
*
Institute for Clinical Evaluative Sciences, Sunnybrook Health Sciences Centre, G-Wing Room 106, University of Toronto, 2075 Bayview Ave., Toronto, Ontario, CanadaM4N 3M5 (nick.daneman@sunnybrook.ca)
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective.

To validate the National Nosocomial Infections Surveillance system risk index through administrative data to predict surgical site infections.

Design.

Retrospective cohort study.

Setting.

Population-based analysis in Ontario, Canada.

Patients.

All elderly patients who underwent elective surgery from April 1, 1992, through March 31, 2006 (n = 469,349).

Methods.

Data on procedural and patient outcomes were gathered from linked population-wide hospital discharge records and physician claims. The 75th percentile of surgical duration was estimated through anesthesiologist billing fees recorded in 15-minute increments; the American Society of Anesthesiology score of at least 3 out of 5 was estimated by diagnostic codes for severe systemic illness; and all surgeries were classified as clean or clean-contaminated because of their elective nature (thus, the maximum score on the modified index was 2).

Results.

A total of 147,216 surgeries (31%) had a score of 0;246,592 (53%) had a score of 1; and 75,541 (16%) had a score of 2 on the modified index. The 30-day risk of surgical site infection increased with each increment in the modified index (score of 0, 5.4%; score of 1, 8.0%; score of 2, 14.3%; P < .001). The association was evident for surgical site infection diagnosed during the index admission (score of 0, 2.0%; score of 1, 3.7%; score of 2, 8.9%; P < .001), as well as that associated with reoperation or death (score of 0, 0.04%; score of 1, 0.23%; score of 2, 0.73%; P < .001). The modified index predicted increases in surgical site infection risk within each of 11 surgical subgroups. In accord with past research, the modified index had modest discrimination (C statistic, 0.59), and the majority of surgical site infections (72%) occurred within lower risk strata.

Conclusions.

The modified index predicts surgical site infection in population-based analyses and is associated with incremental increases in risk.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 30 , Issue 6 , June 2009 , pp. 563 - 569
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Klevens, RM, Edwards, IR, Richards, CL Jr, et al.Estimating healthcare-associated infections and deaths in US hospitals, 2002. Public Health Rep 2007;122:160–166.Google Scholar
2.Haley, RW, Culver, DH, White, JW, et al.The efficacy of infection surveillance and control programs in preventing nosocomial infections in US hospitals. Am J Epidemiol 1985;121:182–205.Google Scholar
3.Mangram, AJ, Horan, TC, Pearson, ML, Silver, LC, Jarvis, WR, Hospital Infection Control Practices Advisory Committee. Guideline for prevention of surgical-site infection, 1999. Am J Infect Control 1999;27:97–132.Google Scholar
4.National Nosocomial Infections Surveillance (NNIS) System Report, data summary from lanuary 1992 through June 2004, issued October 2004. Am I Infect Control 2004;32:470–485.CrossRefGoogle Scholar
5.American Society of Anesthesiologists. New classification of physical status. Anesthesiology 1963;24:111.Google Scholar
6.Culver, DH, Horan, TC, Gaynes, RP, et al.Surgical wound infection rates by wound class, operative procedure, and patient risk index: National Nosocomial Infections Surveillance System. Am J Med 1991;9L152S–157S.Google Scholar
7.Zoutman, DE, Ford, BD, Bryce, E, et al.The state of infection surveillance and control in Canadian acute care hospitals. Am J Infect Control 2003;31:266–272.Google Scholar
8.Delgado-Rodriguez, M, Gomez-Ortega, A, Sillero-Arenas, M, Llorca, J. Epidemiology of surgical-site infections diagnosed after hospital discharge: a prospective cohort study. Infect Control Hosp Epidemiol 2001;22:24–30.CrossRefGoogle ScholarPubMed
9.de Oliveira, AC, Carvalho, DV. Evaluation of underreported surgical-site infection evidenced by postdischarge surveillance. Rev Lat Am Enfer-magem 2007;15:992–997.Google Scholar
10.Avato, JL, Lai, KK. Impact of postdischarge surveillance on surgical-site infection rates for coronary artery bypass procedures. Infect Control Hosp Epidemiol 2002;23:364–367.CrossRefGoogle ScholarPubMed
11.Piatt, R, Yokoe, DS, Sands, KE. Automated methods for surveillance of surgical-site infections. Emerg Infect Dis 2001;7:212–216.Google Scholar
12.Redelmeier, DA, Thiruchelvam, D, Daneman, N. Introducing a methodology for estimating duration of surgery in health services research. J Clin Epidemiol 2008;61:882–889.Google Scholar
13.Tu, IVBowen, I, Chiu, M, et al.Effectiveness and safety of drug-eluting stents in Ontario. N Engl J Med 2007;357:1393–1402.Google Scholar
14.Park-Wyllie, LY, Juurlink, DN, Kopp, A, et al.Outpatient gatifloxacin therapy and dysglycemia in older adults. N Engl J Med 2006;354:1352–1361.Google Scholar
15.Lipscombe, LL, Gomes, T, Levesque, LE, Hux, JE, luurlink, DN, Alter, DA. Thiazolidinediones and cardiovascular outcomes in older patients with diabetes. JAMA 2007;298:2634–2643.Google Scholar
16.Campos, ML, Cipriano, ZM, Freitas, PF. Suitability of the NNIS index for estimating surgical-site infection risk at a small university hospital in Brazil. Infect Control Hosp Epidemiol 2001;22:268–272.Google Scholar
17.Berard, F, Gandon, J. Postoperative wound infections: the influence of ultraviolet irradiation of the operating room and of various other factors. Ann Surg 1964;160(Suppl 2):1–192.Google Scholar
18.Gaynes, RP. Surgical-site infections and the NNIS SSI Risk Index: room for improvement. Infect Control Hosp Epidemiol 2000;21:184–185.Google Scholar
19.Geubbels, EL, Grobbee, DE, Vandenbroucke-Grauls, CM, Wille, JC, de Boer, AS. Improved risk adjustment for comparison of surgical-site infection rates. Infect Control Hosp Epidemiol 2006;27:1330–1339.Google Scholar
20.Friedman, ND, Bull, AL, Russo, PL, Gurrin, L, Richards, M. Performance of the National Nosocomial Infections Surveillance Risk Index in predicting surgical-site infection in Australia. Infect Control Hosp Epidemiol 2007;28:55–59.Google Scholar
21.Thibon, P, Parienti, JJ, Borgey, F, et al.Use of censored data to monitor surgical-site infections. Infect Control Hosp Epidemiol 2002;23:368–371.Google Scholar
22.Cadwallader, HL, Toohey, M, Linton, S, Dyson, A, Riley, TV. A comparison of two methods for identifying surgical-site infections following orthopaedic surgery. J Hosp Infect 2001;48:261–266.Google Scholar
23.Sands, KE, Yokoe, DS, Hooper, DC, et al.Detection of postoperative surgical-site infections: comparison of health plan-based surveillance with hospital-based programs. Infect Control Hosp Epidemiol 2003;24:741–743.Google Scholar
24.Moro, ML, Morsillo, F. Can hospital discharge diagnoses be used for surveillance of surgical-site infections? J Hosp Infect 2004;56:239–241.Google Scholar
25.Whitby, M, McLaws, ML, Collopy, B, et al.Postdischarge surveillance: can patients reliably diagnose surgical wound infections? J Hosp Infect 2002;52:155–160.Google Scholar
26.Petherick, ES, Dalton, JE, Moore, PJ, Cullum, N. Methods for identifying surgical wound infection after discharge from hospital: a systematic review. BMC Infect Dis 2006;6:170.Google Scholar
27.Miner, AL. Enhanced identification of postoperative infections among out Patients. Emerg Infect Dis 2004;10:1931–1937.Google Scholar