317. The social network structure of Oxfordshire hospitals is highly resistant to ward closures
Session: Poster Abstract Session: Assessing and Reducing Infection Risk
Friday, October 21, 2011
Room: Poster Hall B1
  • IDSA_socialnetworks.pdf (420.8 kB)
  • Background:Despite recent developments in theoretical social network modelling, few studies have been undertaken on hospital patient movements. We have applied social network analysis to provide new insights on methods to prevent the  spread of infection.

    Methods:We used an anonymized electronic database of all ward movements in the major Oxfordshire hospitals from January 1998 through June 2010 to construct undirected graphs for patients (where each connection corresponds to shared prior ward exposure) and wards (where connections correspond to patient movements between wards). We estimated a range of network properties from weekly snapshots of the network structure, and compared these with total admissions, discharges, inpatients and ward-flow. Ward closures were artificially simulated within the network to test the effect on the network structure.

    Results:There was a mean (SD) of 3131 (613) admissions and 3131 (611) discharges weekly during the study period; with 3775 (554)inpatients (at any time) during the week, and 987 (202) movements between wards for admitted patients. Network analysis showed that the study hospitals are highly connected ‘scale free’ networks, meaning that a large number of patients (or wards) are “hubs”, showing higher than average connectedness with each other. For patients, the median (IQR) number of shared ward exposures with other patients each week was 42.6 (41.1-44.1), the median (IQR) number of other patients required to link any 2 patients to each other (path length) was 4.8 (4.4-5.1). 91.2% (90.4-95.0) of all patients were linked into one network component; all estimates were stable over time.
    Simulation of the closure of 4 highly connected wards (endoscopy, critical care, medical admissions unit, cardiology) resulted in a maximum change in average path length of only -3.7% and <2.2% of patients were detached from the main network.

    Conclusion:The major Oxfordshire hospitals form a highly robust and stable network in spite of large fluctuations in weekly patient admissions and ward movements supporting continuous transmission of infection. Simulation of ward closures resulted in a minimal impact on network structure and its ability to support transmission of infections.

    Subject Category: N. Hospital-acquired and surgical infections, infection control, and health outcomes including general public health and health services research

    John Finney, Derrick Crook, MB BCh, Tim Peto, MB BS, DPhil and A. Sarah Walker, PhD, NIHR Oxford Biomedical Research Centre, Oxford, United Kingdom


    J. Finney, None

    D. Crook, Optimer: Investigator, Research grant

    T. Peto, Optimer: Scientific Advisor, Consulting fee

    A. S. Walker, None

    Findings in the abstracts are embargoed until 12:01 a.m. EST Thursday, Oct. 20 with the exception of research findings presented at IDSA press conferences.