Leveraging AI in Your GI Practice AI Workshop | September 2025-Understanding AI throughout the Data Lifecycle

Understanding AI throughout the Data Lifecycle

Pdf Summary

In "Understanding AI throughout the Data Lifecycle," Dr. Tyler M. Berzin emphasizes that contemporary gastroenterology (GI) practices function as "data factories," producing vast patient information throughout care. To fully harness this data's potential, practitioners must grasp the entire data lifecycle: from data capture (e.g., endoscopy videos, clinical notes) and curation (cleaning and linking data for coherent patient stories), through modeling (developing AI tools like polyp detection), to deployment (integrating AI into clinical workflows), and finally feedback/outcomes (monitoring tool effectiveness and improving systems).<br /><br />The article highlights evolving AI ecosystems, such as Mayo Clinic’s “AI factory” and major EHR vendors like Epic, which control extensive patient data and plan numerous AI-driven clinical features, aiming to create vertically integrated, closed-loop AI systems in medicine.<br /><br />A critical consideration is balancing AI innovation with patient privacy and ethics. Despite HIPAA allowing de-identified data use without patient consent, ethical stewardship and giving patients a voice in data use remain paramount.<br /><br />GI practices can actively leverage AI opportunities by early evaluation of vendor tools, partnering with disease registries (e.g., CorEvitas), engaging with research/tech platforms supporting clinical trials, and collaborating with health data companies (e.g., Truveta, Flatiron). Different models for data use exist: contributing data to EHR vendors, commercial registries, research partnerships, or forming aggregated “mini-AI factories” across practice networks, enabling revenue generation and innovation control.<br /><br />Ultimately, Dr. Berzin urges GI practices to transition from passive “data donors” to proactive “data stewards.” The strategic choices made now regarding data management and AI integration will determine a practice’s future relevance in the rapidly advancing AI-driven healthcare landscape.

Keywords

AI in gastroenterology

data lifecycle

clinical data management

AI tools in healthcare

patient data privacy

EHR vendors

AI-driven clinical features

data stewardship

clinical AI integration

healthcare data ethics