ABSTRACT: BACKGROUND:When trying to control regional spread of antibiotic-resistant pathogens like carbapenem-resistant Enterobacteriaceae (CRE), decision-makers must choose the highest yield facilities to target for interventions. The question is, with limited resources, how best to choose these facilities. METHODS:Using our Regional Healthcare Ecosystem Analyst-generated agent-based model of all Chicago metropolitan area inpatient facilities, we simulated CRE's spread and different ways of choosing facilities to apply a prevention bundle (screening, chlorhexidine bathing, hand-hygiene, geographic separation, and patient registry) to a resource-limited 1,686 inpatient beds. RESULTS:Randomly selecting facilities did not impact prevalence, but averted 620 new carriers and 175 infections, saving $6.3 million in total costs compared to no intervention. Selecting facilities by type (e.g., LTACHs) yielded a 16.1% relative prevalence decrease, preventing 1,960 cases and 558 infections, saving $62.4 million more than random selection. Choosing the largest facilities was better than random selection, but not than by type. Selecting by considering connections to other facilities (i.e., out-degree) yielded a 9.5% relative prevalence decrease, preventing 1,580 cases, 470 infections, and saving $51.6 million more than random selection. Selecting facilities using a combination of these metrics yielded the greatest reduction (19.0% relative prevalence decrease, preventing 1,840 cases, 554 infections, saving $59.6 million compared to random selection). CONCLUSION:While choosing target facilities based on single metrics (e.g., most inpatient beds, most connections to other facilities) achieved better control than randomly choosing facilities, more effective targeting occurred when considering how these and other factors (e.g., patient length-of-stay, care for higher-risk patients) interacted as a system.