Unsupervised Large Language Models to Identify Topics in Cancer Center Patient Portal Messages

Abstract

PURPOSE: The increasing use of patient portal messages has enhanced patient-provider communication. However, the high volume of these messages has also contributed to physician burnout. METHODS: test. RESULTS: = .04). Scheduling-related messages were the most frequent across departments, whereas symptoms and health concerns were second or third most common topics. In medical oncology and surgical oncology, topics on prescriptions and medications were more common compared with radiation oncology and gynecologic oncology. Despite concurrent institutional changes in self-scheduling systems, scheduling-related messages did not decrease over time. CONCLUSION: The substantial increase in patient portal messages, particularly scheduling-related inquiries, underscores the need for streamlined communication to reduce the burden on health care providers. These findings highlight the need for strategies to manage message volume and mitigate physician burnout, laying groundwork for artificial intelligence-driven future triage systems to improve message management and patient care.

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