CRE are multidrug-resistant bacteria associated with up to 50 percent mortality in infected persons. CRE are increasingly problematic in Illinois healthcare facilities, especially long-term acute care hospitals (LTACHs); therefore, Illinois implemented the eXtensively Drug-Resistant Organism (XDRO) registry (www.xdro. org). Mathematical models have identified patient sharing between healthcare facilities as a mechanism for regional spread, and the importance of each facility within a network can be quantified using social network analysis. Degree centrality is a measure representing the number of facilities with which a facility has shared at least one patient, and hence, a measure of “risk” of receiving a CRE colonized patient. Eigenvector centrality is more sophisticated in that it quantifies how well a given node is connected to other “wellconnected” nodes. We expect that facilities that have high degree and/or eigenvector centrality – and, thus, higher “risk” of encountering a CRE colonized patient – will have higher incidence of CRE, as will facilities that share patients with LTACHs. Understanding facilitylevel characteristics that predict higher CRE rates will enhance the XDRO registry’s usefulness as a surveillance tool.
Objective
To enhance CRE surveillance and communication by incorporating social network measures to quantify patient sharing between facilities.