Improving Diagnostic Safety Through STeatosis Identification, Risk Stratification, and Referral in the ED

Hepatic steatosis is a common radiographic "incidental finding" that is overlooked and underreported to patients. The investigators developed a clinical decision support system using machine learning and natural language processing that will prompt reporting to patients and provide ED clinicians risk stratified follow-up care recommendations. Data on both the implementation and effectiveness of our intervention resulting from this trial will inform future use with a goal of ultimately improving diagnostic safety and outcomes for patients with hepatic steatosis.