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Local Hospital Perspective on a Nationwide Outbreak of Pseudomonas aeruginosa Infection in Norway

Published online by Cambridge University Press:  02 January 2015

Mette Walberg ,
Kathrine Frey Frøslie  and
Jo Røislien
Mette Walberg*
Affiliation:
Microbiology Section, Laboratory Centre, Asker and Baerum Hospital, Rud, Rikshospitalet Medical Centre, Norway Institute of Medical Microbiology, Rikshospitalet Medical Centre, Norway
Kathrine Frey Frøslie
Affiliation:
Biostatistics Group, Research Services Department, Rikshospitalet Medical Centre, Norway
Jo Røislien
Affiliation:
Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Norway
*
Microbiology Section, Laboratory Centre, Asker and Basrum Hospital, 1309 Rud, Norway ([email protected])
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Abstract

Objective.

To implement a system for monitoring of rare events based on statistical process control charts.

Design.

Statistical process control plotting by g chart of clinical microbiology laboratory data.

Setting.

Primary and secondary care Norwegian hospital with a 9-bed intensive care unit.

Results.

During the winter of 2001–2002 in Norway, there was a national monoclonal nosocomial outbreak of Pseudomonas aeruginosa infection mainly affecting patients in intensive care units. In the present work, we demonstrate how the use of SPC at one of the affected hospitals would have detected this outbreak several weeks before the alert from the Norwegian National Public Health Institute (NIPH). By plotting the monthly incidence rate of P. aeruginosa infection (with a c chart), we found that the hospital would have been alerted in February, by plotting the number of days between events (with a g chart), we found that the hospital would have detected a process already out of control in early January 2002. Not until 9 weeks later (ie, mid-March) did the NIPH declare the P. aeruginosa outbreak to be national, and a commercially produced mouth swab contaminated during the manufacturing process was found to be the source.

Conclusion.

The plotting of rare events, such as an outbreak of nosocomial infection, with a g chart may be used for early detection of a process out of control.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 29 , Issue 7 , July 2008 , pp. 635 - 641
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2008

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