DonnaRosa Project: Exploring Informal Communication Practices Among Breast Cancer Specialists

Background: Healthcare communication often relies on complex digital infrastructures, yet clinicians increasingly adopt general-purpose Instant Messaging Apps (IMAs) such as WhatsApp® to meet unmet needs. DonnaRosa, an Italian community of breast cancer specialists founded in 2017, is a Community of Practice (CoP), where experts exchange second opinions, guidelines, and trial opportunities. This paper examines its origins, practices, and implications. Methods: A mixed-methods design was applied: (1) qualitative analysis of chat logs to identify interaction patterns and rules; (2) a 2024 online survey of 54 members (92.5% response rate) exploring demographics, usage, and perceived value; (3) ongoing semi-structured interviews with founders and participants to reconstruct history, recruitment, and professional impact. Results: The group has grown through personal invitations, creating a friendly network of oncologists. Communication is concise, colloquial, and collegial. Activities focus on case discussions, reassurance, interpretation of guidelines, and exchange of research opportunities. This article presents data from an online survey conducted in 2024, showing that the group is widely used for second opinions, often consulted even on weekends and holidays, and perceived as a source of professional support and learning. Members report that participation frequently changes or refines their clinical judgement, especially when guidelines are incomplete or ambiguous. The community also promotes resilience, reduces professional isolation, supports informal collaboration in research projects, and encourages interaction on organisational and healthcare management issues. Conclusions: DonnaRosa illustrates how informal IMAs can evolve into robust infrastructures of care and professional solidarity, complementing formal systems. In the era of artificial intelligence, CoPs like DonnaRosa may become even more relevant: AI tools, especially large language models, can accelerate literature retrieval and data synthesis, while the CoP provides the critical, experience-based interpretation needed for safe and meaningful application. Such a dual infrastructure—technological and human—offers a promising path for oncology, where complexity requires both computational breadth and the depth of expert clinical judgement. Taken together, these findings and the evolving role of AI in clinical communication underscore the need for oncology societies to develop governance frameworks that ensure the safe, accountable, and clinically appropriate use of instant-messaging tools in professional practice.