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An Intranet-Based Automated System for the Surveillance of Nosocomial Infections: Prospective Validation Compared with Physicians' Self-Reports

Published online by Cambridge University Press:  02 January 2015

Samir Bouam ,
Emmanuelle Girou ,
Christian Brun-Buisson ,
Harry Karadimas  and
Eric Lepage
Samir Bouam
Affiliation:
Département de Biostatistiques et d‘Information Hospitalier, Hôpital Henri Mondor, Assistance Publique–Hôpitaux de Paris, Créteil, France
Emmanuelle Girou*
Affiliation:
Unité d'Hygiène et Prévention de l'Infection, Hôpital Henri Mondor, Assistance Publique–Hôpitaux de Paris, Créteil, France
Christian Brun-Buisson
Affiliation:
Unité d'Hygiène et Prévention de l'Infection, Hôpital Henri Mondor, Assistance Publique–Hôpitaux de Paris, Créteil, France
Harry Karadimas
Affiliation:
Département de Biostatistiques et d‘Information Hospitalier, Hôpital Henri Mondor, Assistance Publique–Hôpitaux de Paris, Créteil, France
Eric Lepage
Affiliation:
Département de Biostatistiques et d‘Information Hospitalier, Hôpital Henri Mondor, Assistance Publique–Hôpitaux de Paris, Créteil, France
*
Unité d'Hygiène et Prévention de l'Infection, Hôpital Henri Mondor, 94010 Créteil, France
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Abstract

Objective:

To examine the reliability of the data produced by an automated system for the surveillance of nosocomial infections.

Setting:

A 906-bed, tertiary-care teaching hospital.

Design:

Three surveillance techniques were concurrently performed in seven high-risk units during an 11-week period: automated surveillance (AS) based on the prospective processing of computerized medical records; laboratory-based ward surveillance (LBWS) based on the retrospective verification by ward clinicians of weekly reports of positive bacteriologic results; and a reference standard (RS) consisting of the infection control team reviewing case records of patients with positive bacteriology results. Bacteremia, urinary tract infections, and catheter-related infections were recorded for all inpatients. The performances (sensitivity, specificity, and time consumption) of AS and LBWS were compared with those of RS.

Results:

Of 548 positive bacteriology samples included during the study period, 229 (42%) were classified as nosocomial infections. The overall sensitivity was 91% and 59% for AS and LBWS, respectively. The two methods had the same overall specificity value (91%). Kappa measures of agreement were 0.81 and 0.54 for AS and LBWS, respectively. AS required less time to collect data (54 seconds per week per unit) compared with LBWS (7 minutes and 43 seconds per week per unit) and RS (37 minutes and 15 seconds per week per unit).

Conclusion:

Our results confirm that the retrospective review of charts and laboratory data by physicians lacks sensitivity for the surveillance of nosocomial infections. The intranet-based automated method developed for this purpose was more accurate and less time-consuming than the weekly, retrospective LBWS method.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 24 , Issue 1 , January 2003 , pp. 51 - 55
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2003

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References

1.Scheckler, WE, Brimhall, D, Buck, AS, et al. Requirements for infrastructure and essential activities of infection control and epidemiology in hospitals: a consensus panel report. Infect Control Hosp Epidemiol 1998;19:114–124.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
3.Ministère de l'Emploi et de la Solidarité. Décret n° 99–1034 du 6 décembre 1999 relatif à l'organisation de la lutte contre les infections nosoco-miales dans les établissements de santé. Journal Officiel de la République Française 1999;287;18439–18440.Google Scholar
4.Secrétariat d'Etat à la Santé. Circulaire DGS/DHOS n°645 du 29 décembre 2000 relative à l'organisation de la lutte contre les infections nosocomiales dans les établissements de santé. Bulletin Officiel de la République Française 2001;3:312–321.Google Scholar
5.Agence Nationale d'Accréditation et d'Evaluation en Santé. Manuel d'accréditation des établissements de santé. Agence Nationale d'Accréditation et d'Evaluation en Santé; 1999.Google Scholar
6.Perl, TM. Surveillance, reporting, and the use of computers. In: Wenzel, RP, ed. Prevention and Control of Nosocomial Infections, 2nd ed. Baltimore: Williams & Wilkins; 1993:139–176.Google Scholar
7.Bouam, S, Girou, E, Brun-Buisson, C, Lepage, E. Development of a web-based clinical information system for surveillance of multiresistant organisms and nosocomial infections.Proc AMIA Symp 1999;January:696–700.Google ScholarPubMed
8.Comité Technique National des Infections Nosocomiales. 100 Recommandations pour la Surveillance et la Prévention des Infections Nosocomiales. Paris, France: Ministère de l'Emploi et de la Solidarité; 1999.Google Scholar
9.Garner, J, Jarvis, WR, Emori, TG, Horan, TC, Hughes, JM. CDC definitions for nosocomial infections. Am J Infect Control 1988;16:128–140.CrossRefGoogle ScholarPubMed
10.Brun-Buisson, C, Abrouk, F, Legrand, P, Huet, Y, Larabi, S, Rapin, M. Diagnosis of central venous catheter-related sepsis: critical level of quantitative tip culture. Arch Intern Med 1987;147:873–877.CrossRefGoogle Scholar
11.Birnbaum, D, Sheps, SB. Validation of new tests. Infect Control Hosp Epidemiol 1991;12:622–624.CrossRefGoogle ScholarPubMed
12.Cohen, J. A coefficient of agreement for nominal scales. Educ Psychol Meas 1960;20:37–46.CrossRefGoogle Scholar
13.Fleiss, JL. Statistical Methods for Rates and Proportions, 2nd ed. New York: Wiley; 1981.Google Scholar
14.Glenister, H, Taylor, L, Bartlett, C, Cooke, M, Sedgwick, J, Mackintosh, CA. An evaluation of surveillance methods for detecting infections in hospital inpatients. J Hosp Infect 1993;23:229–242.CrossRefGoogle ScholarPubMed
15.Belio-Blasco, C, Torres-Fernández-Gil, MA, Echeverría-Echarri, JL, Gomez-Lopez, LI. Evaluation of two retrospective active surveillance methods for the detection of nosocomial infection in surgical patients. Infect Control Hosp Epidemiol 2000;21:24–27.CrossRefGoogle ScholarPubMed
16.Boulétreau, A, Dettenkofer, M, Forster, DH, et al. Comparison of effectiveness and required time of two surveillance methods in intensive care patients. J Hosp Infect 1999;41:281–289.CrossRefGoogle ScholarPubMed
17.Evans, RS, Larsen, RA, Burke, JP, Gardner, RM, Meier, FA, Jacobson, JA. Computer surveillance of hospital-acquired infections and antibiotic use. JAMA 1986;256:1007–1111.CrossRefGoogle ScholarPubMed
18.Kahn, MG, Steib, SA, Fraser, VJ, Dunagan, WC. An expert system for culture-based infection control surveillance. Proc Annu Symp Comput Appi Med Care 1993;171–175.Google ScholarPubMed
19.Willard, KE, Johnson, JR, Connelly, DP. Radical improvements in the display of clinical microbiology results: a Web-based clinical information system. Am J Med 1996;101:541–549.CrossRefGoogle ScholarPubMed