Abstract: A method, computer program product, and computing system for: accessing a first siloed dataset concerning one or more medical notes; processing the first siloed dataset to identify clinical items within the one or more medical notes, thus defining a first tagged clinical item set; selecting a first set of templates for the first siloed dataset based, at least in part, upon the first tagged clinical item set within the first siloed dataset; defining a first instruct dataset for the first siloed dataset based, at least in part upon the first set of templates and first tagged clinical item set; and training a generative model using the first instruct dataset, thus defining a generative model trained for the first siloed dataset.

Abstract: A method, computer program product, and computing system for processing target content generated by processing source content using a generative artificial intelligence (AI) model, where the generative AI model performs a task using the source content to generate the target content. An ontological concept is extracted from the source content using a natural language processing (NLP) engine. An ontological concept is extracted from the target content using the NLP engine. An ontological concept comparison score is generated by comparing the ontological concept from the source content and the ontological concept from the target content based upon, at least in part, the task performed using the source content to generate the target content. An issue is identified in the target content based upon, the ontological concept comparison score and the task performed using the source content to generate the target content.