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A Model-Based Strategy to Control the Spread of Carbapenem-Resistant Enterobacteriaceae: Simulate and Implement

Published online by Cambridge University Press:  09 September 2016

Mirian de Freitas DalBen*
Affiliation:
Infection Control Department and LIM54, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil Department of Infectious Diseases and Institute of Tropical Medicine, University of São Paulo, São Paulo, Brazil
Elisa Teixeira Mendes
Affiliation:
Infection Control Department and LIM54, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil Department of Infectious Diseases and Institute of Tropical Medicine, University of São Paulo, São Paulo, Brazil
Maria Luisa Moura
Affiliation:
Infection Control Department and LIM54, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
Dania Abdel Rahman
Affiliation:
Infection Control Department and LIM54, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
Driele Peixoto
Affiliation:
Infection Control Department and LIM54, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
Sania Alves dos Santos
Affiliation:
Infection Control Department and LIM54, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil Department of Infectious Diseases and Institute of Tropical Medicine, University of São Paulo, São Paulo, Brazil
Walquiria Barcelos de Figueiredo
Affiliation:
Nursing Division, Faculty of Medicine, Hospital das Clinicas, University of São Paulo, São Paulo, Brazil
Pedro Vitale Mendes
Affiliation:
Intensive Care Unit, Emergency Medicine Discipline, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
Leandro Utino Taniguchi
Affiliation:
Intensive Care Unit, Emergency Medicine Discipline, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
Francisco Antonio Bezerra Coutinho
Affiliation:
Discipline of Medical Informatics, School of Medicine, University of São Paulo, São Paulo, Brazil
Eduardo Massad
Affiliation:
Discipline of Medical Informatics, School of Medicine, University of São Paulo, São Paulo, Brazil
Anna Sara Levin
Affiliation:
Infection Control Department and LIM54, Hospital das Clínicas, University of São Paulo, São Paulo, Brazil Department of Infectious Diseases and Institute of Tropical Medicine, University of São Paulo, São Paulo, Brazil
*
Address correspondence to Mirian F. DalBen, MD, Department of Infection Control of Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Rua Frei Caneca, 640/252-Vereda, São Paulo, Brazil 01307-000 ([email protected]).

Abstract

OBJECTIVE

To reduce transmission of carbapenem-resistant Enterobacteriaceae (CRE) in an intensive care unit with interventions based on simulations by a developed mathematical model.

DESIGN

Before-after trial with a 44-week baseline period and 24-week intervention period.

SETTING

Medical intensive care unit of a tertiary care teaching hospital.

PARTICIPANTS

All patients admitted to the unit.

METHODS

We developed a model of transmission of CRE in an intensive care unit and measured all necessary parameters for the model input. Goals of compliance with hand hygiene and with isolation precautions were established on the basis of the simulations and an intervention was focused on reaching those metrics as goals. Weekly auditing and giving feedback were conducted.

RESULTS

The goals for compliance with hand hygiene and contact precautions were reached on the third week of the intervention period. During the baseline period, the calculated R0 was 11; the median prevalence of patients colonized by CRE in the unit was 33%, and 3 times it exceeded 50%. In the intervention period, the median prevalence of colonized CRE patients went to 21%, with a median weekly Rn of 0.42 (range, 0–2.1).

CONCLUSIONS

The simulations helped establish and achieve specific goals to control the high prevalence rates of CRE and reduce CRE transmission within the unit. The model was able to predict the observed outcomes. To our knowledge, this is the first study in infection control to measure most variables of a model in real life and to apply the model as a decision support tool for intervention.

Infect Control Hosp Epidemiol 2016;1–8

Type
Original Articles
Copyright
© 2016 by The Society for Healthcare Epidemiology of America. All rights reserved 

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References

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