Clinical pre-consultation, where patients share health information prior to an appointment, offers a pathway to more patient-centered care by freeing time for meaningful patient–physician conversations. Conversational agents powered by large language models (LLMs) can automate this process to make it more scalable and consistent, but this risks producing information overload that exacerbates physicians’ workload as they spend time parsing through data. This paper examines the opportunities and challenges of using conversational agents to mediate the transfer of information between patients and physicians, with the aim of producing clinically useful, patient-driven pre-consultation summaries to capture their histories and concerns. Through sessions with both physicians and patients, we show that such a summary can increase patient confidence and sense of control over their health information while fostering a more collaborative dynamic. We conclude with design recommendations for integrating pre-consultation agents into clinical workflows.
ACM CHI Conference on Human Factors in Computing Systems