2107. Integrating Prior Healthcare Exposure into National Mandatory Clostridium difficile Infection Surveillance
Session: Poster Abstract Session: Clostridium difficile: Risk Factors
Saturday, October 29, 2016
Room: Poster Hall
Posters
  • CDI_PriorHCExposure_2107.pdf (633.2 kB)
  • Background: In 2014 recommendations were published in England to update the ‘Time to Onset’ algorithm used in national mandatory Clostridium difficile infection (CDI) surveillance (Figure 1a) to align it with other international definitions (e.g. Center for Disease Control; European Centre for Disease Control). This reduces the days used to identify a healthcare onset (HO) case (from 3 to 2 days post admission) and adds a prior healthcare exposure element for community onset (CO) cases (Figure 1b). The new algorithm comes into effect in Financial Year (FY) 2017/18. Here we describe the impact of changes to case distribution and review the strategy to implement the new definitions into national surveillance and associated public reporting. Methods: Hospital groups (Trusts) have limited information on complex patient pathways prior to CDI diagnosis. CDI cases were linked to Hospital Episode Statistics (HES), data of all admissions in England, to establish prior healthcare exposures. A comparison of HO CDI cases from existing versus updated ‘Time to Onset’ algorithms using FY 2014/15 data was completed. Results: Reducing the number of days used to define HO CDI leads to a 17% increase for FY 2014/15 (n=5,145 to n=6,038 HO CDI cases). Preliminary HES linkage shows 53% of CO cases are healthcare associated (Figure 2). However, access to HES data takes ~6 months, leading to unacceptable delays in public reporting. As the great majority (89%) of CO cases with prior interactions occurred in the same Trust that reported the CDI, a self-reporting strategy is favoured. Workflow processes of surveillance were evaluated and adapted to accommodate the new algorithm, which then informed software development. Results from the HES linkage will be disseminated to Trusts providing previous CDI trends using the new algorithm prior to switchover in FY 2017/18. Conclusion: The high percentage of CO cases with prior healthcare interactions occurring ‘within Trust’ supports the intention to limit reports to prior interactions at the same Trust. This approach balances the need to update the CDI ‘Time to Onset’ algorithm with practicalities of routine data availability at a national level.  
    John Davies, MPH1, Sarah Gerver, PhD1, Alan Johnson, PhD2, Mark Wilcox, MD3 and Russell Hope, PhD1, (1)Healthcare Associated Infection & Antimicrobial Resistance, Public Health England, London, United Kingdom, (2)National Infection Service, Public Health England, London, United Kingdom, (3)University of Leeds, Leeds, United Kingdom

    Disclosures:

    J. Davies, None

    S. Gerver, None

    A. Johnson, None

    M. Wilcox, MERCK: Grant Investigator , Scientific Advisor and Speaker's Bureau , Consulting fee , Research support and Speaker honorarium
    PFIZER: Grant Investigator , Scientific Advisor and Speaker's Bureau , Consulting fee , Research support and Speaker honorarium
    SUMMIT: Grant Investigator and Scientific Advisor , Consulting fee and Research support
    SERES: Grant Investigator , Scientific Advisor and Speaker's Bureau , Consulting fee , Research support and Speaker honorarium
    DA VOLTERRA: Grant Investigator and Scientific Advisor , Consulting fee and Research support
    BIOMERIEUX: Investigator and Scientific Advisor , Consulting fee and Research support
    ALERE: Grant Investigator , Scientific Advisor and Speaker's Bureau , Consulting fee , Research support and Speaker honorarium
    ACTELION: Grant Investigator and Scientific Advisor , Consulting fee and Research support

    R. Hope, None

    Findings in the abstracts are embargoed until 12:01 a.m. CDT, Wednesday Oct. 26th with the exception of research findings presented at the IDWeek press conferences.