This session highlights how Mayo Clinic Arizona addressed gaps in capturing and reporting Social Determinants of Health (SDOH) to improve data accuracy and population health insights. Attendees will learn how integrating validated psychosocial assessment data with natural language processing (NLP) technology enabled more consistent identification and coding of SDOH diagnoses. The presentation outlines how this approach streamlined workflows for CDI and coding professionals, reducing manual variation while improving efficiency and accuracy. Early results demonstrate enhanced coding performance, reduced burden on staff, and stronger alignment with CMS requirements and health equity goals. Participants will leave with practical insights into leveraging technology and standardized processes to better capture SDOH data and support organizational outcomes.

This session offers 1 AHIMA CEU.