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

Enrolling by invitation · Not applicable

Conditions studied: Non-Alcoholic Fatty Liver Disease, Steatosis of Liver, Metabolic Dysfunction-Associated Steatotic Liver Disease

In brief

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.

Key facts

Study ID

NCT06944353

Run by

Northwestern University

People needed

4704

Starts

2025-12-04

Expected to finish

2028-07-01

Last updated by the study team

2026-05-29

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• imaging finding of hepatic steatosis on ED imaging study
• discharged from the ED to home
• first Northwestern Medicine ED visit in the study period with a hepatic steatosis finding

You may not qualify if…

• admitted to the hospital
• age < 18
• pre-existing Liver Disease diagnosis (Liver Cancer, HCV, HBV, Cirrhosis, NAFLD/MASLD/NASH/MASH, Alcohol Liver Disease, PSC, PBC and autoimmune hepatitis)

Where it is running

• Northwestern Memorial Hospital — Chicago, Illinois, United States

Full record on ClinicalTrials.gov

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