As the demand for timely, high-quality oncology data grows, hospital-based registries face mounting pressure to streamline operations while maintaining timeliness, accuracy, and completeness. Advances in artificial intelligence (AI), natural language processing (NLP), and machine learning (ML) are opening new pathways to enhance casefinding, abstracting, follow up and reporting functions. In this webinar, we will explore how these emerging technologies can be integrated into daily registry workflows to increase productivity and support data-driven clinical, operational and research efforts. By the end of this webinar, participants will be able to:

1.  Define at least five key terms and concepts used to describe AI-powered technology such as artificial intelligence, natural language processing, and machine learning.

2.  Describe how automation enhances each of the core registry functions, including case-finding, abstracting, follow-up, quality control and performance improvement.

3.  Outline the process of selecting and implementing an AI-powered software solution, including selecting the team of stakeholders, conducting a workflow gap analysis, and engaging leadership in the evaluation, selection, and        implementation of the solution

4.  Identify and discuss common operational and cultural barriers to adoption, and explore strategies for overcoming resistance, redesigning workflows, and maximizing team engagement.

5.  Illustrate how real-time data and advanced automation tools drive accreditation, elevate quality improvement efforts, accelerate research, and empower clinical decision-making in Commission on Cancer (CoC) accredited facilities

This webinar is designed for cancer registry leaders and data quality coordinators both at the hospital and state level, but all ODS-credentialed cancer registry professionals are welcome to register.