Hostname: page-component-8448b6f56d-c4f8m Total loading time: 0 Render date: 2024-04-18T19:14:36.376Z Has data issue: false hasContentIssue false

Complex Surgical Site Infections and the Devilish Details of Risk Adjustment: Important Implications for Public Reporting

Published online by Cambridge University Press:  02 January 2015

Deverick J. Anderson*
Affiliation:
Duke Infection Control Outreach Network, Duke University Medical Center, Durham, North Carolina
Luke F. Chen
Affiliation:
Duke Infection Control Outreach Network, Duke University Medical Center, Durham, North Carolina
Daniel J. Sexton
Affiliation:
Duke Infection Control Outreach Network, Duke University Medical Center, Durham, North Carolina
Keith S. Kaye
Affiliation:
Duke Infection Control Outreach Network, Duke University Medical Center, Durham, North Carolina
*
Duke University Medical Center, Box 3605, Durham, NC 27710 (dja@duke.edu)

Abstract

Objective.

To validate the National Nosocomial Infection Surveillance (NNIS) risk index as a tool to account for differences in case mix when reporting rates of complex surgical site infection (SSI).

Design.

Prospective cohort study.

Setting.

Twenty-four community hospitals in the southeastern United States.

Methods.

We identified surgical procedures performed between January 1, 2005, and June 30, 2007. The Goodman-Kruskal gamma or G statistic was used to determine the correlation between the NNIS risk index score and the rates of complex SSI (not including superficial incisional SSI). Procedure-specific analyses were performed for SSI after abdominal hysterectomy, cardiothoracic procedures, colon procedures, insertion of a hip prosthesis, insertion of a knee prosthesis, and vascular procedures.

Results.

A total of 2,257 SSIs were identified during the study period (overall rate, 1.19 SSIs per 100 procedures), of which 1,093 (48.4%) were complex (0.58 complex SSIs per 100 procedures). There were 45 complex SSIs identified following 7,032 abdominal hysterectomies (rate, 0.64 SSIs per 100 procedures); 63 following 5,318 cardiothoracic procedures (1.18 SSIs per 100 procedures); 139 following 5,144 colon procedures (2.70 SSIs per 100 procedures); 63 following 6,639 hip prosthesis insertions (0.94 SSIs per 100 procedures); 73 following 9,658 knee prosthesis insertions (0.76 SSIs per 100 procedures); and 55 following 6,575 vascular procedures (0.84 SSIs per 100 procedures). All 6 procedure-specific rates of complex SSI were significantly correlated with increasing NNIS risk index score (P< .05).

Conclusions.

Some experts recommend reporting rates of complex SSI to overcome the widely acknowledged detection bias associated with superficial incisional infection. Furthermore, it is necessary to compensate for case-mix differences in patient populations, to ensure that intrahospital comparisons are meaningful. Our results indicate that the NNIS risk index is a reasonable method for the risk stratification of complex SSIs for several commonly performed procedures.

Type
Original Article
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2008

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.Birnbaum, D. Mandatory public reporting. Clin Governance 2008;13:142146.Google Scholar
2.Garner, JS, Jarvis, WR, Emori, TG, Horan, TC, Hughes, JM. CDC definitions for nosocomial infections, 1988. Am J Infect Control 1988;16:128140.Google Scholar
3.McKibben, L, Horan, T, Tokars, JI, et al.Guidance on public reporting of healthcare-associated infections: recommendations of the Healthcare Infection Control Practices Advisory Committee. Am J Infect Control 2005;33:217226.Google Scholar
4.Wong, ES, Rupp, ME, Mermel, L, et al.Public disclosure of healthcare-associated infections: the role of the Society for Healthcare Epidemiology of America. Infect Control Hosp Epidemiol 2005;26:210212.CrossRefGoogle ScholarPubMed
5.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;91 (3B):152S157S.Google Scholar
6.National Nosocomial Infections Surveillance (NNIS) System Report, data summary from January 1992 through June 2004, issued October 2004. Am J Infect Control 2004;32:470485.Google Scholar
7.Petrosillo, N, Drapeau, CM, Nicastri, E, Martini, L, Ippolito, G, Moro, ML. Surgical site infections in Italian hospitals: a prospective multicenter study. BMC Infect Dis 2008;8:34.Google Scholar
8.National Voluntary Consensus Standards for the Reporting of Healthcare-associated Infections Data. National Quality Forum, 2007. Available at: http://www.qualityforum.org/projects/ongoing/hai/index.asp). Accessed March 10, 2008.Google Scholar
9.Gaynes, RP, Culver, DH, Horan, TC, Edwards, JR, Richards, C, Tolson, JS. Surgical site infection (SSI) rates in the United States, 1992-1998: the National Nosocomial Infections Surveillance System basic SSI risk index. Clin Infect Dis 2001; 33(Suppl 2):S69S77.Google Scholar
10.Consensus paper on the surveillance of surgical wound infections. The Society for Hospital Epidemiology of America; The Association for Practitioners in Infection Control; The Centers for Disease Control; The Surgical Infection Society. Infect Control Hosp Epidemiol 1992;13:599605.Google Scholar
11.Kaye, KS, Sloane, R, Sexton, DJ, Schmader, KA. Risk factors for surgical site infections in older people. J Am Ceriatr Soc 2006;54:391396.Google Scholar
12.Kaye, KS, Engemann, JJ, Fulmer, EM, Clark, CC, Noga, EM, Sexton, DJ. Favorable impact of an infection control network on nosocomial infection rates in community hospitals. Infect Control Hosp Epidemiol 2006;27:228232.Google Scholar
13.Bratzler, DW, Hunt, DR. The surgical infection prevention and surgical care improvement projects: national initiatives to improve outcomes for patients having surgery. Clin Infect Dis 2006;43:322330.Google Scholar
14. Mandatory public reporting of healthcare-associated infections, 2007. Available at: http://www.apic.org. Accessed March 10, 2008.Google Scholar
15.Engemann, JJ, Carmeli, Y, Cosgrove, SE, et al.Adverse clinical and economic outcomes attributable to methicillin resistance among patients with Staphylococcus aureus surgical site infection. Clin Infect Dis 2003;36:592598.Google Scholar
16.Kirkland, KB, Briggs, JP, Trivette, SL, Wilkinson, WE, Sexton, DJ. The impact of surgical-site infections in the 1990s: attributable mortality, excess length of hospitalization, and extra costs. Infect Control Hosp Epidemiol 1999;20:725730.Google Scholar
17.Yokoe, DS, Noskin, GA, Cunnigham, SM, et al.Enhanced identification of postoperative infections among inpatients. Emerg Infect Dis 2004;10:19241930.Google Scholar
18.Mangram, AJ, Horan, TC, Pearson, ML, Silver, LC, Jarvis, WR. Guideline for Prevention of Surgical Site Infection, 1999. Centers for Disease Control and Prevention (CDC) Hospital Infection Control Practices Advisory Committee. Am J Infect Control 1999;27:97132.CrossRefGoogle ScholarPubMed
19.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
20.Barnes, S, Salemi, C, Fithian, D, et al.An enhanced benchmark for prosthetic joint replacement infection rates. Am J Infect Control 2006;34:669672.Google Scholar
21.Mannien, J, van den Hof, S, Brandt, C, Behnke, M, Wille, JC, Gastmeier, P. Comparison of the National Surgical Site Infection surveillance data between The Netherlands and Germany: PREZIES versus KISS. J Hosp Infect 2007;66:224231.Google Scholar
22.Essentials of Public Reporting of Healthcare-Associated Infections: A Tool Kit. 2007. Available at: http://www.shea-online.org/Assets/files/Essentials_of_Public_Reporting_Tool_Kit.pdf. Accessed April 1, 2008.Google Scholar
23.Paul, M, Raz, A, Leibovici, L, Madar, H, Holinger, R, Rubinovitch, B. Sternal wound infection after coronary artery bypass graft surgery: validation of existing risk scores. J Thorac Cardiovasc Surg 2007;133:397403.CrossRefGoogle ScholarPubMed
24.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;21:186190.Google Scholar
25.Russo, PL, Spelman, DW. A new surgical-site infection risk index using risk factors identified by multivariate analysis for patients undergoing coronary artery bypass graft surgery. Infect Control Hosp Epidemiol 2002;23:372376.CrossRefGoogle ScholarPubMed
26.Friedman, ND, Bull, AL, Russo, PL, et al.An alternative scoring system to predict risk for surgical site infection complicating coronary artery bypass graft surgery. Infect Control Hosp Epidemiol 2007;28:11621168.Google Scholar
27.Brandt, C, Hansen, S, Sohr, D, Daschner, F, Ruden, H, Gastmeier, P. Finding a method for optimizing risk adjustment when comparing surgical-site infection rates. Infect Control Hosp Epidemiol 2004;25:313318.Google Scholar
28.Clements, AC, Tong, EN, Morton, AP, Whitby, M. Risk stratification for surgical site infections in Australia: evaluation of the US National Nosocomial Infection Surveillance risk index. J Hosp Infect 2007;66:148155.Google Scholar
29.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;27:13301339.Google Scholar
30.Batista, R, Kaye, K, Yokoe, DS. Admission-specific chronic disease scores as alternative predictors of surgical site infection for patients undergoing coronary artery bypass graft surgery. Infect Control Hosp Epidemiol 2006;27:802808.Google Scholar
31.Kaye, KS, Schmit, K, Pieper, C, et al.The effect of increasing age on the risk of surgical site infection. J Infect Dis 2005;191:10561062.Google Scholar