Hostname: page-component-7479d7b7d-68ccn Total loading time: 0 Render date: 2024-07-08T20:46:01.621Z Has data issue: false hasContentIssue false
  • English
  • Français

Nosocomial Infection Surveillance in a Surgical Intensive Care Unit in Spain, 1996-2000: A Time-Trend Analysis

Published online by Cambridge University Press:  21 June 2016

Máxima Lizán-Garcia ,
Ramón Peyro ,
Manuel Cortiña ,
María Dolores Crespo  and
Aurelio Tobias
Máxima Lizán-Garcia*
Affiliation:
Servicio de Medicina Preventiva, Complejo Hospitalario y Universitario de Albacete, Albacete, Spain
Ramón Peyro
Affiliation:
Unidad de Reanimación, Complejo Hospitalario y Universitario de Albacete, Albacete, Spain
Manuel Cortiña
Affiliation:
Servicio de Medicina Preventiva, Complejo Hospitalario y Universitario de Albacete, Albacete, Spain Unidad de Reanimación, Complejo Hospitalario y Universitario de Albacete, Albacete, Spain
María Dolores Crespo
Affiliation:
Servicio de Microbiologia, Complejo Hospitalario y Universitario de Albacete, Albacete, Spain
Aurelio Tobias
Affiliation:
Statistics Department, Complejo Hospitalario y Universitario de Albacete, Albacete, Spain Mathematics Department, Universitat Autonoma, Barcelona, Spain
*
Servicio Medicina Preventiva/Hospital General, C/ Hermanos Falco 3, 2001 Albacete, Spain ([email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective.

To establish the occurrence, distribution, and secular time trend of nosocomial infections (NIs) in a surgical intensive care unit (ICU).

Design and Setting.

Follow-up study in a teaching hospital in Spain.

Methods.

In May 1995 we established an nosocomial infection surveillance system in our surgical ICU. We collected information daily for all patients who were in the ICU for at least 48 hours (546 patients from 1996 through 2000). We used the Centers for Disease Control and Prevention definitions and criteria for infections. Monthly, we determined the site-specific incidence densities of NIs, the rates of medical device use, and the Poisson probability distribution, which determined whether the case count equalled the number of expected cases (the mean number of cases during the previous year, with extreme values excluded). We compared yearly and monthly infection rates by Poisson regression, using site-specific NIs as a dependent variable and year and month as dummy variables. We tested annual trends with an alternative Poisson regression model fitting a single linear trend.

Results.

The average rate of catheter-associated urinary tract infections was 8.4 per 1000 catheter-days; that of ventilator-associated pneumonia, 21 per 1000 ventilator-days; and that of central line–associated bloodstream infections, 30 per 1000 central line–days. The rate of urinary tract infections did not change over the study period, but there was a trend toward decreases in the rates of central line–associated bloodstream infections and ventilator-associated pneumonia.

Conclusion.

An NI surveillance and control program contributed to a progressive decrease in NI rates.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 27 , Issue 1 , January 2006 , pp. 54 - 59
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2006

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.Fridkin, SK, Welbel, SF, Weinstein, RA. Magnitude and prevention of nosocomial infections in the intensive care unit. Infect Dis Clin North Am 1997; 11:479–496.Google Scholar
2.Pallavicini, F, Pennisi, MA, Izzi, I, et al. Nosocomial infection rates in an Italian intensive care unit using the national nosocomial infection surveillance system. Infect Control Hosp Epidemiol 2001; 22:132–133.Google Scholar
3.Fernandez-Crehuet, R, Diaz-Molina, C, de Irala, J, Martinez-Concha, D, Salcedo-Leal, I, Masa-Calles, J. Nosocomial infection in an intensive-care unit: identification of risk factors. Infect Control Hosp Epidemiol 1997; 18:825–830.Google Scholar
4.Grupo de Trabajo de Enfermedades Infecciosas de la Sociedad Española de Medicina Intensiva Critica y Unidades Coronarias. Estudio Nacional de Vigilancia e Infección Nosocomial en Servicios de Medicina Intensiva. Informe 2000.Google Scholar
5.National Nosocomial Infection Surveillance (NNIS) System Report, Data Summary from January 1992-June 2001, issued August 2001. Am J Infect Control 2001;29:404–421.Google Scholar
6.Venberghe, A, Laterre, P, Goenen, M, et al. Surveillance of hospital-acquired infection in an intensive care department-the benefit of the full-time presence of an infection control nurse. J Hosp Infect 2002;52:56–59.Google Scholar
7.Jamulitrat, S, Narong, MN, Thongpiyapoom, S. Trauma severity scoring systems as predictors of nosocomial infection. Infect Control Hosp Epidemiol 2002; 23:268–273.CrossRefGoogle ScholarPubMed
8.Urli, T, Perone, G, Acquarolo, A, Zappa, S, Antonini, B, Ciani, A. Surveillance of infections acquired in intensive care: usefulness in clinical practice. J Hosp Infect 2002; 52:130–135.Google Scholar
9.Jarvis, WR, Edwards, JR, Culver, DH, et al. Nosocomial infection rates in adult and pediatric intensive care units in the United States. National Nosocomial Infections Surveillance System. Am J Med 1991; 91(3B): 185S–191S.Google Scholar
10.Centers for Disease Control and Prevention. Updated Guidelines for evaluating public health surveillance systems: recommendations from the Guidelines Working Group. MMWR 2001; 50(RR-13):1–35.Google Scholar
11.Pottinger, JM, Herwaldt, L, Peri, TM. Basics of surveillance: an overview. In: Herwaldt, LA, Decker, MD / The Society for Healthcare Epidemiology of America, ed. A Practical Handbook for Hospital Epidemiologists. Thorofare, NJ: Slack; 1998.Google Scholar
12.Decker, MD, Sprouse, MW. Hospitalwide Surveillance Activities, 158-192. In: Wenzel, RP, ed. Assessing Quality Health Care. Perspectives for Clinicians. Baltimore, MD: Williams & Wilkins, 1992:158–192.Google Scholar
13.Ely, JW, Dawson, JD, Lemke, JH, Rosenberg, J. An introduction to time-trend analysis. Infect Control Hosp Epidemiol 1997; 18:267–274.Google Scholar
14.Perez-Hoyos, S, Ballester, F, Tenias, JM. Uso de la regresión de Poisson para la detección de casos en series temporales de enfermedades de declaración obligatoria con pocos casos semanales. Gac Sanit 1999; 13(Suppl 2):33–68.Google Scholar
15.Beck-Sague, C, Jarvis, WR, Martone, WJ. Outbreak investigations. Infect Control Hosp Epidemiol 1997; 18:138–145.Google Scholar
16.Frome, EL. The analysis of rates using Poisson regression models. Biometrics 1983; 39:665–674.CrossRefGoogle ScholarPubMed
17.Delgado-Rodriguez, M, Gomez-Ortega, A, Sillero-Arenas, M, Martinez-Gallego, G, Medina-Cuadros, M, Llorca, J. Efficacy of surveillance in nosocomial infection control in a surgical service. Am J Infect Control 2001; 29:289–294.Google Scholar
18.Frome, EL, Checkoway, H. Epidemiologic programs for computers and calculators. Use of Poisson regression models in estimating incidence rates and ratios. Am J Epidemiol 1985; 121:309–323.CrossRefGoogle ScholarPubMed
19.Merino, JM, Moreno, E, Padilla, M, Rodríguez-Miñon, P, Villarino, A. Distribuciones discretas de probabilidad 566-569, EN: Análisis de datos en Psicología I UNE, Madrid 2001.Google Scholar
20.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.CrossRefGoogle Scholar
21.Fridkin, SK, Pear, SM, Williamson, TH, Galgiani, JN, Jarvis, WR. The role of understaffing in central venous catheter-associated bloodstream infections. Infect Control Hosp Epidemiol 1996; 17:150–158.Google Scholar
22.Robert, J, Fridkin, SK, Blumberg, HM, et al. The influence of the composition of the nursing staff on primary bloodstream infection rates in a surgical intensive care unit. Infect Control Hosp Epidemiol 2000; 21:12–17.Google Scholar
23.Alonso-Echanove, J, Edwards, JR, Richards, MJ, et al. Effect of nurse staffing and antimicrobial-impregnated central venous catheters on the risk for bloodstream infections in intensive care unit. Infect Control Hosp Epidemiol 2003; 24:916–925.Google Scholar