Hostname: page-component-848d4c4894-ndmmz Total loading time: 0 Render date: 2024-05-14T03:13:07.663Z Has data issue: false hasContentIssue false

Use of Censored Data to Monitor Surgical-Site Infections

Published online by Cambridge University Press:  02 January 2015

Pascal Thibon*
Affiliation:
Réseau Régional d'Hygiène de Basse-Normandie, France Service d'Hygiène Hospitalière, CHU de Caen, France
J. J. Parienti
Affiliation:
Service d'Hygiène Hospitalière, CHU de Caen, France
F. Borgey
Affiliation:
Réseau Régional d'Hygiène de Basse-Normandie, France Service d'Hygiène Hospitalière, CH d'Avranches-Granville, France
A. Le Prieur
Affiliation:
Réseau Régional d'Hygiène de Basse-Normandie, France Service d'Hygiène Hospitalière, CH de Lisieux, France
C. Bernet
Affiliation:
Réseau Régional d'Hygiène de Basse-Normandie, France Service d'Hygiène Hospitalière, CHU de Caen, France
B. Branger
Affiliation:
C-CLIN Ouest, CHU de Rennes, France
X. Le Coutour
Affiliation:
Réseau Régional d'Hygiène de Basse-Normandie, France Service d'Hygiène Hospitalière, CHU de Caen, France
*
Service d'Hygiène Hospitalière, niveau 1, CHU de Caen, 14033 Caen Cedex, France

Abstract

Objective:

To take into account the proportion of patients lost to follow-up when calculating surgical-site infection (SSI) rates.

Design:

A multicenter SSI monitoring network in Basse-Normandie, France, using the definitions for SSI of the National Nosocomial Infections Surveillance System of the Centers for Disease Control and Prevention.

Patients:

Between January 1, 1998, and December 31, 1999, 3,705 patients were operated on in 25 units of 10 institutions.

Results:

Of the patients, 41.2% (range, 5.1% to 95.5%) were seen 30 days or more after their operation. The global SSI attack rate was 2.19% (95% confidence interval, 1.72% to 2.66%). With the use of the Kaplan–Meier method, the incidence rate was 3.11% (95% confidence interval, 3.06% to 3.16%). The difference between the attack rate and the Kaplan–Meier incidence rate for each unit varied according to the percentage of patients seen on or after day 30 postoperatively and the number of SSIs diagnosed in patients seen on or after day 30.

Conclusions:

Practice guidelines are needed for the international monitoring for postdischarge SSIs and the calculation of SSI rates. The proportion of patients seen 30 days after their operation is a major quality criterion for SSI monitoring and should be routinely given in monitoring reports, oral communications, and publications to compare results obtained by different teams.

Type
Original Articles
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2002

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.Gaynes, RP. Surveillance of surgical-site infections: the world coming together? Infect Control Hosp Epidemiol 2000;21:309310.Google Scholar
2.Smyth, ETM, Emmerson, AM. Surgical site infection surveillance. J Hosp Infect 2000;45:173184.Google Scholar
3.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;13:606608.CrossRefGoogle ScholarPubMed
4.Garver, JS, Jarvis, WR, Emori, TG, Horan, TC, Hughes, JM. CDC definitions for nosocomial infections, 1988. Am J Infect Control 1988; 16:128140.Google Scholar
5.Mertens, R, Van den Berg, JM, Veerman-Brenzikofer, MLV, Kurz, X, Jans, B, Klaanga, N. International comparison of results of infection surveillance: The Netherlands versus Belgium. Infect Control Hosp Epidemiol 1994;15:574580.CrossRefGoogle ScholarPubMed
6.Byrne, DJ, Lynch, W, Napier, A, Davey, P, Malek, M, Cuschieri, A. Wound infection rates: the importance of definition and post-discharge wound surveillance. J Hosp Infect 1994;26:3743.Google Scholar
7.Ministère de l'Emploi et de la Solidarité. Circulaire DGS/VS/VS2-DH/E01 - n°17 du 19 avril 1995 relative à la lutte contre les infections nosocomiales dans les établissements de santé publics ou privés participant à l'exécution du service public. Ministère de l'Emploi et de la Solidarité, Secrétariat d'Etat à la Santé et l'Action Sociale; 1995.Google Scholar
8.Comité Technique National des Infections Nosocomiales. 100 recommandations pour la surveillance et la prévention des infections nosocomiales, 2nd ed. Ministère de l'Emploi et de la Solidarité, Secrétariat d'Etat à la Santé et l'Action Sociale; 1999.Google Scholar
9.Lee, ET. Nonparametric methods of estimating survival functions. In: Lee, ET, ed. Statistical Methods for Survival Date Analysis. New York: John Wiley & Sons; 1992:66103.Google Scholar
10.Couto, RC, Pedrosa, TM, Nogueira, JM, Gomes, DL, Neto, MF, Rezende, NA. Post-discharge surveillance and infection rates in obstetric patients. Int J Gynaecol Obstet 1998;61:227231.Google Scholar
11.Manian, FA, Meyer, L. Adjunctive use of monthly physician questionnaires for surveillance of surgical site infections after hospital discharge and in ambulatory surgical patients: report of a seven-year experience. Am J Infect Control 1997;25:390394.Google Scholar
12.Seaman, M, Lammers, R. Inability of patients to self-diagnose wound infections. J Emerg Med 1991;9:215219.Google Scholar
13.Mitchel, DH, Swift, G, Gilbert, GL. Surgical wound infection surveillance: the importance of infections that develop after hospital discharge. Aust NZJ Surg 1999;69:117120.CrossRefGoogle Scholar
14.Sands, K, Vineyard, G, Platt, R. Surgical site infections occurring after hospital discharge. J Infect Dis 1996;173:963970.Google Scholar