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A Comparison Between National Healthcare Safety Network Laboratory-Identified Event Reporting versus Traditional Surveillance for Clostridium difficile Infection

Published online by Cambridge University Press:  22 December 2014

Michael J. Durkin ,
Arthur W. Baker ,
Kristen V. Dicks ,
Sarah S. Lewis ,
Luke F. Chen ,
Deverick J. Anderson ,
Daniel J. Sexton  and
Rebekah W. Moehring
Michael J. Durkin*
Affiliation:
Department of Medicine, Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina, USA Duke Infection Control Outreach Network, Durham, North Carolina, USA Duke Program for Infection Prevention and Healthcare Epidemiology, Durham, North Carolina, USA
Arthur W. Baker
Affiliation:
Department of Medicine, Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina, USA Duke Infection Control Outreach Network, Durham, North Carolina, USA Duke Program for Infection Prevention and Healthcare Epidemiology, Durham, North Carolina, USA
Kristen V. Dicks
Affiliation:
Department of Medicine, Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina, USA Duke Infection Control Outreach Network, Durham, North Carolina, USA Duke Program for Infection Prevention and Healthcare Epidemiology, Durham, North Carolina, USA
Sarah S. Lewis
Affiliation:
Department of Medicine, Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina, USA Duke Infection Control Outreach Network, Durham, North Carolina, USA Duke Program for Infection Prevention and Healthcare Epidemiology, Durham, North Carolina, USA
Luke F. Chen
Affiliation:
Department of Medicine, Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina, USA Duke Infection Control Outreach Network, Durham, North Carolina, USA Duke Program for Infection Prevention and Healthcare Epidemiology, Durham, North Carolina, USA
Deverick J. Anderson
Affiliation:
Department of Medicine, Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina, USA Duke Infection Control Outreach Network, Durham, North Carolina, USA Duke Program for Infection Prevention and Healthcare Epidemiology, Durham, North Carolina, USA
Daniel J. Sexton
Affiliation:
Department of Medicine, Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina, USA Duke Infection Control Outreach Network, Durham, North Carolina, USA Duke Program for Infection Prevention and Healthcare Epidemiology, Durham, North Carolina, USA
Rebekah W. Moehring
Affiliation:
Department of Medicine, Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina, USA Duke Infection Control Outreach Network, Durham, North Carolina, USA Duke Program for Infection Prevention and Healthcare Epidemiology, Durham, North Carolina, USA Durham Veterans Affairs Medical Center, Durham, North Carolina, USA
*
Address correspondence to Michael J. Durkin, MD, Division of Infectious Diseases, Duke University Medical Center, Hanes House 315 Trent Drive, Durham, NC (michael.durkin@dm.duke.edu).
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Abstract

OBJECTIVE

Hospitals in the National Healthcare Safety Network began reporting laboratory-identified (LabID) Clostridium difficile infection (CDI) events in January 2013. Our study quantified the differences between the LabID and traditional surveillance methods.

DESIGN

Cohort study.

SETTING

A cohort of 29 community hospitals in the southeastern United States.

METHODS

A period of 6 months (January 1, 2013, to June 30, 2013) of prospectively collected data using both LabID and traditional surveillance definitions were analyzed. CDI events with mismatched surveillance categories between LabID and traditional definitions were identified and characterized further. Hospital-onset CDI (HO-CDI) rates for the entire cohort of hospitals were calculated using each method, then hospital-specific HO-CDI rates and standardized infection ratios (SIRs) were calculated. Hospital rankings based on each CDI surveillance measure were compared.

RESULTS

A total of 1,252 incident LabID CDI events were identified during 708,551 patient-days; 286 (23%) mismatched CDI events were detected. The overall HO-CDI rate was 6.0 vs 4.4 per 10,000 patient-days for LabID and traditional surveillance, respectively (P<.001); of 29 hospitals, 25 (86%) detected a higher CDI rate using LabID compared with the traditional method. Hospital rank in the cohort differed greatly between surveillance measures. A rank change of at least 5 places occurred in 9 of 28 hospitals (32%) between LabID and traditional CDI surveillance methods, and for SIR.

CONCLUSIONS

LabID surveillance resulted in a higher hospital-onset CDI incidence rate than did traditional surveillance. Hospital-specific rankings varied based on the HO-CDI surveillance measure used. A clear understanding of differences in CDI surveillance measures is important when interpreting national and local CDI data.

Infect Control Hosp Epidemiol 2014;00(0): 1–7

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 36 , Issue 2 , February 2015 , pp. 125 - 131
Copyright
© 2014 by The Society for Healthcare Epidemiology of America. All rights reserved 

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Footnotes

Previous Presentation: A preliminary report of this research was presented at IDWeek, October 2–6, 2013. San Francisco, CA. Abstract 41953.

References

REFERENCES

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