Reimagining Multidisciplinary Teams: Challenges and Opportunities for LLMs in Cancer MDTs

Abstract

Multidisciplinary teams are crucial in tailoring cancer care through collaborative decision-making involving several clinical specialties. The inherent complexity of clinical cases, the increasing abundance of unstructured textual data, and the time restrictions of professionals pose significant challenges to team coordination and patient care. This creates an opportunity for generative AI technologies, such as LLMs, to enhance collaborative work. Despite the growing interest in HCI research to explore LLMs in healthcare, we have yet to understand clinicians' perspectives on this emerging technology in multidisciplinary teams. Our work investigates the challenges, expectations and opportunities for LLMs in this context through a speculative approach. We leveraged the Futures Cone framework and conducted a qualitative study with 11 physicians from different cancer multidisciplinary teams. We contribute with an analysis of themes that emerged from individual interviews and a focus group, highlighting LLMs' potential to enhance and reshape multidisciplinary teams' practices. In addition, we uncover concerns and coping strategies related to LLMs' adoption and provide a set of design opportunities to inform the development of technologies for LLM-enhanced multidisciplinary teams.

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