Using Mandatory Data Collection on Multiresistant Bacteria for Internal Surveillance in a Hospital

U. Sagel; R. T. Mikolajczyk; A. Krämer

doi:10.1055/s-0038-1633903

Methods of Information in Medicine, Table of Contents

Methods Inf Med 2004; 43(05): 483-485
DOI: 10.1055/s-0038-1633903

Original Article

Schattauer GmbH

Using Mandatory Data Collection on Multiresistant Bacteria for Internal Surveillance in a Hospital

Authors

U. Sagel

¹Institute of Microbiology and Infectious Diseases Epidemiology of Gilead/Mara Hospitals, Bielefeld, Germany
R. T. Mikolajczyk

²Department of Public Health Medicine, School of Public Health, University of Bielefeld, Germany
A. Krämer

²Department of Public Health Medicine, School of Public Health, University of Bielefeld, Germany

Abstract

Summary

Objectives: Multiresistant pathogens cause major clinical problems and considerably increase treatment costs. Since 2001 the Protection Against Infection Act (PIA) obligates hospitals in Germany to the documentation of multiresistant bacteria. We analyzed the use of these data for routine internal surveillance.

Methods: We used standard data collected for the mandatory documentation and studied consecutive diagnoses of Methicillin-resistant Staphylococcus aureus (MRSA) in a 893-bed tertiary level hospital in North Rhine-Westphalia in Germany. Based on the Poisson distribution for the cumulative yearly incidence of MRSA, we defined a threshold level for an outbreak.

Results: During a 12-month time period 80 patients were diagnosed with MRSA. The time structure and spatial distribution of different MRSA phenotypes (defined through specific antibiotic resistance patterns) were consistent with the within-hospital transmission. In the two preceding time periods of 12 months each, 15 respectively 8 patients with MRSA were found. The defined alert threshold level for cumulative yearly incidence was crossed in the beginnings of the outbreak.

Conclusion: Monitoring the mandatory data collected on multiresistant bacteria allows the early detection of accumulations suspect for the within-hospital transmission. This knowledge can be used for a fast reaction and breaking off the transmission chains.

Keywords

Nosocomial infection - multiresistant pathogens - surveillance

Full Text

References

References
1 Vincent JL. Nosocomial infections in adult intensive- care units. Lancet 2003; 361: 2068-77.
2 Anonymous. Surveillance of nosocomial infections and recording of pathogens with specific resistances and multiresistances [German]. Bundesgesundheitsbl – Gesundheitsforsch – Gesundheitsschutz 2000; 43: 887-90.
3 Pfaller MA, Acar J, Jones RN, Verhoef J, Turnidge J, Sador HS. Integration of molecular characterization of microorganisms in a global antimicrobial resistance surveillance program. Clin Infect Dis 2001; 32: S156.67
4 Tenover FC, Arbeit RD, Goering RV. editors How to Select and Interpret Molecular Strain Typing Methods for Epidemiological Studies of Bacterial Infections: A Review for Healthcare Epidemiologists. Infect Control Hosp Epidemiol 1997; 18: 426-39.
5 Anonymous. Staphylococcal infections in Germany in 2002 [German]. Epidemiol Bull 2003; 35: 277-80.
6 Witte W, Braulke Ch, Heuck D. MRSA-situation in Germany: Appearance, distribution and changes in virulent epidemic strains of MRSA with different resistance phenotypes [German]. Hyg Med 2000; 25 (09) 347-50.
7 Grundmann H, Hori S, Tanner G. Determining Confidence Intervals when Measuring Genetic Diversity and the Discriminatory Abilities of Typing Methods for Microorganisms. J Clin Microbiol 2001; 39: 4190-2.
8 Austin DJ, Bonten MJM, Weinstein RA, Slaughter S, Anderson R. Vancomycin-resistant enterococci in intensive-care hospital setting: Transmission dynamics, persistence, and the impact of infection control programs. Proc Natl. Acad Sci 1999; 96: 6908-13.
9 Pelupessy I, Bonten MJM, Diekmann O. How to assess the relative importance of different colonization routes of pathogens within hospital settings. Proc Natl Acad Sci 2002; 99: 5601-5.
10 Brown SM, Benneyan JC, Theobald DA, Sands K, Hahn MT, Potter-Bynoe GA, Stelling JM, O’Brien TF, Goldmann DA. Binary Cumulative Sums and Moving Averages in Nosocomial Infection Cluster Detection. Emerg Infect Dis 2002; 8: 1426-32.
11 Hacek DM, Suriano T, Noskin GA, Kruszynski JA, Reisberg BE, Peterson LR. Medical and economic benefit of a comprehensive infection control program that includes routine determination of microbial clonality. Am J Clin Pathol 1999; 111: 647-54.
12 Ngo L, Tager IB, Hadley D. Application of exponential smoothing for nosocomial infection surveillance. Am J Epidemiol 1996; 143: 637-47.
13 Farrington CP, Andrews NJ, Beale AD, Catchpole MA. A statistical algorithm for the early detection of outbreaks of infectious disease. Journal of the Royal Statistical Society Series A 1996; 159: 547-63.
14 Hoeck MRI. et al. Bacterial pathogens of hospital infections with special resistances and multiresistances. Part II. Recording and Evaluation according to § 23 PIA in a regional network [German]. Bundesgesundheitsbl – Gesundheitsforsch – Gesundheitsschutz 2004; 47: 363-8.