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

  • Michael J. Durkin (a1) (a2) (a3), Arthur W. Baker (a1) (a2) (a3), Kristen V. Dicks (a1) (a2) (a3), Sarah S. Lewis (a1) (a2) (a3), Luke F. Chen (a1) (a2) (a3), Deverick J. Anderson (a1) (a2) (a3), Daniel J. Sexton (a1) (a2) (a3) and Rebekah W. Moehring (a1) (a2) (a3) (a4)...
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

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

Footnotes
References
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1. Miller, BA, Chen, LF, Sexton, DJ, Anderson, DJ. Comparison of the burdens of hospital-onset, healthcare facility-associated Clostridium difficile infection and of healthcare-associated infection due to methicillin-resistant Staphylococcus aureus in community hospitals. Infect Control Hosp Epidemiol 2011;32:387390.
2. Antibiotic Resistance Threats in the United States. 2013. Center for Disease Control and Prevention website. http://www.cdc.gov/drugresistance/threat-report-2013/pdf/ar-threats-2013-508.pdf. Published 2013. Accessed September 30, 2013.
3. Gase, KA, Haley, VB, Xiong, K, Van Antwerpen, C, Stricof, RL. Comparison of 2 Clostridium difficile surveillance methods: National Healthcare Safety Network’s laboratory-identified event reporting module versus clinical infection surveillance. Infect Control Hosp Epidemiol 2013;34:284290.
4. Illinois Statewide Report of Clostridium difficile infections in Acute Care Hospitals, NHSN Reporting January 1, 2012 – December 31, 2012. Illinois Department of Public Health website. http://www.healthcarereportcard.illinois.gov/files/pdf/C_diff_IL_acute_hosp_NHSN_2012_final.pdf. Published June 2013. Accessed September 30, 2013.
5. Anderson, DJ, Miller, BA, Chen, LF, et al. The network approach for prevention of healthcare-associated infections: long-term effect of participation in the Duke Infection Control Outreach Network. Infect Control Hosp Epidemiol 2011;32:315322.
6. McDonald, LC, Coignard, B, Dubberke, E, et al. Recommendations for surveillance of Clostridium difficile-associated disease. Infect Control Hosp Epidemiol 2007;28:140145.
7. Multidrug-Resistant Organism & Clostridium difficile Infection (MDRO/CDI) Module. Centers for Disease Control and Prevention website. http://www.cdc.gov/nhsn/PDFs/pscManual/12pscMDRO_CDADcurrent.pdf. Published January 2014. Accessed September 13, 2014.
8. Risk Adjustment for Healthcare Facility-Onset C. difficile and MRSA Bacterermia Laboratory-identified Event Reporting in NHSN. Centers for Disease Control and Prevention website. http://www.cdc.gov/nhsn/PDFs/mrsa-cdi/RiskAdjustment-MRSA-CDI.pdf. Published March 2013. Accessed November 7, 2014.
9. Your Guide to the Standardized Infection Ratio (SIR). National Healthcare Safety Network e-News Special Edition. Centers for Disease Control and Prevention website. http://www.cdc.gov/nhsn/PDFs/Newsletters/NHSN_NL_OCT_2010SE_final.pdf. Published October 2010. Accessed November 7, 2014.
10. Moehring, RW, Lofgren, ET, Anderson, DJ. Impact of change to molecular testing for Clostridium difficile infection on healthcare facility-associated incidence rates. Infect Control Hosp Epidemiol 2013;34:10551061.
11. Jury, L SB, Stiefel, , Donskey, CJ. How smart is the chart? Diarrhea, documentation, fecal incontinence, and Clostridium difficile infection. IDWeek 2012. Abstract #360. Published October 12, 2012.
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Infection Control & Hospital Epidemiology
  • ISSN: 0899-823X
  • EISSN: 1559-6834
  • URL: /core/journals/infection-control-and-hospital-epidemiology
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