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. 2017 Aug 15;65(4):581-587.
doi: 10.1093/cid/cix370.

The Potential for Interventions in a Long-term Acute Care Hospital to Reduce Transmission of Carbapenem-Resistant Enterobacteriaceae in Affiliated Healthcare Facilities

Damon J A Toth  1   2 , Karim Khader  1   2 , Rachel B Slayton  3 , Alexander J Kallen  3 , Adi V Gundlapalli  1   2 , Justin J O'Hagan  3 , Anthony E Fiore  3 , Michael A Rubin  1   2 , John A Jernigan  3 , Matthew H Samore  1   2
Affiliations

The Potential for Interventions in a Long-term Acute Care Hospital to Reduce Transmission of Carbapenem-Resistant Enterobacteriaceae in Affiliated Healthcare Facilities

Damon J A Toth et al. Clin Infect Dis. .

Abstract

Background: Carbapenem-resistant Enterobacteriaceae (CRE) are high-priority bacterial pathogens targeted for efforts to decrease transmissions and infections in healthcare facilities. Some regions have experienced CRE outbreaks that were likely amplified by frequent transmission in long-term acute care hospitals (LTACHs). Planning and funding of intervention efforts focused on LTACHs is one proposed strategy to contain outbreaks; however, the potential regional benefits of such efforts are unclear.

Methods: We designed an agent-based simulation model of patients in a regional network of 10 healthcare facilities including 1 LTACH, 3 short-stay acute care hospitals (ACHs), and 6 nursing homes (NHs). The model was calibrated to achieve realistic patient flow and CRE transmission and detection rates. We then simulated the initiation of an entirely LTACH-focused intervention in a previously CRE-free region, including active surveillance for CRE carriers and enhanced isolation of identified carriers.

Results: When initiating the intervention at the first clinical CRE detection in the LTACH, cumulative CRE transmissions over 5 years across all 10 facilities were reduced by 79%-93% compared to no-intervention simulations. This result was robust to changing assumptions for transmission within non-LTACH facilities and flow of patients from the LTACH. Delaying the intervention until the 20th CRE detection resulted in substantial delays in achieving optimal regional prevalence, while still reducing transmissions by 60%-79% over 5 years.

Conclusions: Focusing intervention efforts on LTACHs is potentially a highly efficient strategy for reducing CRE transmissions across an entire region, particularly when implemented as early as possible in an emerging outbreak.

Keywords: active surveillance; carbapenem-resistant Enterobacteriaceae; long-term acute care hospital; mathematical model; transmission.

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Conflict of interest statement

Potential conflicts of interest. A. V. G. has received personal fees from Promise Hospital of Salt Lake. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

Figures

Figure 1.
Figure 1.
Facility network. Area of each circle is proportional to the average patient/resident population of the facility. Outgoing arrows from each facility refer to the facilities that receive most (but not necessarily all) of the transfer patients out of the facility. All facilities also discharge patients to the community, and all facilities admit patients from the community except for the long-term acute care hospital, which only admits transfer patients from the short-stay acute care hospitals. Abbreviations: ACH, short-stay acute care hospital; LTACH, long-term acute care hospital; NH, nursing home.
Figure 2.
Figure 2.
Long-term implications for delaying the start of intervention (both components) on average regional facility prevalence of carbapenem-resistant Enterobacteriaceae (CRE). Points are average prevalence at each year (horizontally offset for clarity) after initial CRE introduction for no intervention (circles); intervention initiation triggered at 1 clinical detection in the long-term acute care hospital (triangles) and at 20 clinical detections (squares). Vertical lines are 90% variability ranges across 1000 stochastic simulations. Left panel: model A; right panel: model B.
See this image and copyright information in PMC

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