Characterizing nursing home care team communication via text messaging: A social network analysis

• Social network analysis of 5,092 text messages and 585 nursing home-to-hospital transfers. • Three network typologies emerged: Integrated (highly connected), Hub-and-Spoke (centralized), and Siloed (role-specific) • Informal opinion leaders, not formal authority, drove communication patterns in electronic messaging networks. • Network structure may influence care coordination, quality, and innovation adoption in nursing homes. Communication breakdowns among healthcare teams contribute substantially to preventable adverse events in nursing homes. Although text messaging platforms are increasingly used to support care coordination, little is known about how these technologies are embedded within care team communication networks. The purpose of this study was to characterize patterns of text-message communication among nursing home care teams and to examine how network structures reflect underlying social system dynamics. Social network analysis was applied to text messages (n = 5,092) linked to (n = 585) nursing home-to-hospital resident transfers over 5 years (2015–2020). Message metadata and content were used to construct communication networks and to calculate network measures, including density, centralization (in-degree and out-degree), and reciprocity. Networks were qualitatively classified into communication models based on shared structural characteristics and interpreted using Rogers’ Diffusion of Innovations theory. All analysis and visualization was conducted using Python (3.13.9). Three distinct communication models were identified. The Integrated model exhibited high message volume, high connectivity, and low hierarchy, consistent with mature adoption of text messaging as a general collaboration tool. The Hub-and-Spoke model showed moderate message volume with centralized information flow, reflecting protocol-driven, hierarchical communication. The Siloed model demonstrated high message volume but low role diversity, indicating niche use within specific professional roles rather than facility-wide coordination. Across models, individuals occupying central or bridging positions appeared to function as informal opinion leaders, influencing communication through frequent interaction rather than formal authority. The structure and quality of communication networks shape how information flows, influence is exercised through electronic messaging, and innovations are integrated into care processes. Social network analysis offers a rigorous approach for evaluating implementation and guiding strategies to support effective, team-based communication in nursing home settings. Future work should examine whether increasingly integrated communication networks are associated with improved resident outcomes.