Objectives. I used computational models to test the relationship between interorganizational network structures and diffusion of moderate- to high-priority health information throughout a system. I examined diffusion effects of mean and variance in organizational partnering tendencies, arrangement of ties among subgroups of the system, and the diffusing organization’s effective network size. Methods. I used agent-based models to simulate local information-sharing processes and observe the outcomes of system-level diffusion. Graphs of diffusion curves demonstrated differences among intergroup structures, and regression models were used to test effects of parameterized and emergent network variables on diffusion. Results. The average tendency of participating organizations to engage in partnerships with other network members influenced diffusion of information, but variance in partnering tendencies had little effect. Fully connected subgroup structures outperformed hierarchical connections among subgroups, and all outperformed group-to-group chains. Introduction of a small proportion of randomness in connections among members of the chain structure improved diffusion without increasing network density. Finally, greater effective size in the diffusing organization’s network increased diffusion of information. Conclusions. Small interventions that build connecting structures among subgroups within a health system can be particularly effective at facilitating natural dissemination of information.