We quantify the transmission dynamics of VRE faecium in a hospital and relationships between these dynamics and the evolution of antibiotic resistance. We estimated the rates of infection import and between-patient transmission by fitting a transmission model to longitudinal patient screening data by maximum likelihood. We then used these migration and transmission rates, and four years of detailed patient movement data to parameterize an agent-based simulation of transmission. Predictions of this model include the number, size, and structure of transmission clusters within the hospital. We tested these predictions by comparing them with clusters of within-hospital transmission constructed from whole-genome sequences of 86 VRE faecium isolates. Finally, we looked for resistance evolution within and across transmission clusters using antimicrobial susceptibility testing to the antibiotic daptomycin. Our results show that this hospital system is close to a dynamic threshold of maintaining transmission, i.e., an R0 close to 1, suggesting that a small decrease in transmission may lead to a dramatic drop in prevalence. We suggest that resistance evolution may be driven both by the differential transmissibility of resistant and sensitive strains as well as by the of evolution of resistance within clusters. Our findings frame an approach to resistance management strategies to slow or reverse the evolution of resistance in this pathogen by quantifying the relative importance of infection prevention and antimicrobial stewardship.