Colorectal cancer (CRC) is the second most common cause of cancer-related mortality, killing over 50,000 Americans each year – a number that is unwarranted as it many of these cases are preventable via screening and surveillance of high-risk abnormalities. For instance, many people with high-risk polyps that are detected during initial colonoscopies fail to follow-up in a timely manner.  Often such findings are not fully documented and/or issues exist with inconsistencies in reporting, making it challenging to definitively know which patients need to come back and when. Working with investigators in the Division of Digestive Diseases, the Center for SMART Health is helping to identify these individuals at UCLA through automated natural language processing (NLP) tools, looking to merge colonoscopy and pathology report observations in the electronic health record (EHR) into a comprehensive picture that can then be used to guide follow-up recommendations.