AI-Enhanced Otolaryngology: A Discussion on Large Language Model Applications in Clinical Practice and Education

PROGRAM DESCRIPTION: Artificial intelligence, particularly Large Language Models (LLMs), is revolutionizing healthcare delivery. This session provides a practical, evidence-based framework for implementing AI tools to enhance patient education, streamline clinical workflows, and optimize pre- and postoperative care.

We will demonstrate real-world applications including: personalized multilingual patient education materials, automated pre-visit preparation guidance and customized post-operative instruction generation. The focus will be on how LLMs can address common challenges in otolaryngology practice, such as improving patient understanding of complex procedures, reducing pre-appointment anxiety, and enhancing adherence to post-operative care instructions.

The presentation will showcase live demonstrations of AI implementations in clinical scenarios, including:
- Pre-visit information gathering and patient education
- Procedure-specific preparation guides and expectations
- Automated post-operative care instructions with interactive troubleshooting
- Multilingual communication tools for diverse patient populations
- Integration of AI tools into existing clinical workflows

Attendees will gain practical knowledge about implementing these technologies while maintaining high standards of patient care. We will address critical considerations including patient privacy, information accuracy, and cost-effectiveness.

OUTCOME OBJECTIVE 1: Integrate LLM capabilities into existing clinical workflows to streamline patient communication efficiency, and enhance quality of patient educational materials.

OUTCOME OBJECTIVE 2: Develop AI-assisted multilingual communication strategies to enhance patient education across diverse populations, including customized materials for common procedures and treatment plans.

OUTCOME OBJECTIVE 3: Implement AI-powered tools to create personalized pre-visit information packets and post-operative care instructions that improve patient understanding and adherence while reducing staff workload.

BACKGROUND STATEMENT: The rapid adoption of AI and LLMs requires guidance for MDs to implement these tools safely and effectively. With increasing patient demand for accessible information and growing administrative burden, AI can enhance patient education and streamline workflow while maintaining quality care.

Comprehensive Otolaryngology Track Statement : AI can assist comprehensive otolaryngologist's need to manage diverse conditions efficiently. These tools support holistic care by generating patient education materials and instructions, while improving practice efficiency across all aspects of ENT care.