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Journal Article
Research Support, U.S. Gov't, P.H.S.
Evaluating Movement of Patients With Carbapenem-resistant Enterobacteriaceae Infections in the Greater Atlanta Metropolitan Area Using Social Network Analysis.
Clinical Infectious Diseases 2020 January 2
BACKGROUND: Carbapenem-resistant Enterobacteriaceae (CRE) are an urgent threat with potential for rapid spread. We evaluated the role of Medicare patient movement between facilities to model the spread of CRE within a region.
METHODS: Through population-based CRE surveillance in the 8-county Atlanta (GA) metropolitan area, all Escherichia coli, Enterobacter spp., or Klebsiella spp. resistant to ≥1 carbapenem were reported from residents. CRE was attributed to a facility based on timing of culture and facility exposures. Centrality metrics were calculated from 2016 Medicare data and compared to CRE-transfer derived centrality metrics by Spearman correlation.
RESULTS: During 2016, 283 incident CRE cases with concurrent or prior year facility stays were identified; cases were attributed mostly to acute care hospitals (ACHs; 141, 50%) and skilled nursing facilities (SNFs; 113, 40%), and less frequently to long-term acute care hospitals (LTACHs; 29, 10%). Attribution was widespread, originating at 17 of 20 ACHs (85%), 7 of 8 (88%) LTACHs, but only 35 of 65 (54%) SNFs. Betweenness of Medicare patient transfers strongly correlated with betweenness of CRE case-transfer data in ACHs (r = 0.75; P < .01) and LTACHs (r = 0.77; P = .03), but not in SNFs (r = 0.02; P = 0.85). We noted 6 SNFs with high CRE-derived betweenness but low Medicare-derived betweenness.
CONCLUSIONS: CRE infections originate from almost all ACHs and half of SNFs. We identified a subset of SNFs central to the CRE transfer network but not the Medicare transfer network; other factors may explain CRE patient movement in these facilities.
METHODS: Through population-based CRE surveillance in the 8-county Atlanta (GA) metropolitan area, all Escherichia coli, Enterobacter spp., or Klebsiella spp. resistant to ≥1 carbapenem were reported from residents. CRE was attributed to a facility based on timing of culture and facility exposures. Centrality metrics were calculated from 2016 Medicare data and compared to CRE-transfer derived centrality metrics by Spearman correlation.
RESULTS: During 2016, 283 incident CRE cases with concurrent or prior year facility stays were identified; cases were attributed mostly to acute care hospitals (ACHs; 141, 50%) and skilled nursing facilities (SNFs; 113, 40%), and less frequently to long-term acute care hospitals (LTACHs; 29, 10%). Attribution was widespread, originating at 17 of 20 ACHs (85%), 7 of 8 (88%) LTACHs, but only 35 of 65 (54%) SNFs. Betweenness of Medicare patient transfers strongly correlated with betweenness of CRE case-transfer data in ACHs (r = 0.75; P < .01) and LTACHs (r = 0.77; P = .03), but not in SNFs (r = 0.02; P = 0.85). We noted 6 SNFs with high CRE-derived betweenness but low Medicare-derived betweenness.
CONCLUSIONS: CRE infections originate from almost all ACHs and half of SNFs. We identified a subset of SNFs central to the CRE transfer network but not the Medicare transfer network; other factors may explain CRE patient movement in these facilities.
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