Assessing Performance of a Hepatitis C Emergency Department (HepC-EnD) Screening Tool: IT Integration Process for Electronic Health Record System

Starting soon

Conditions studied: Hepatitis C Virus (HCV), Hepatitis C Virus (HCV) Infection, HIV (Human Immunodeficiency Virus)

In brief

The goal of this observational study is to develop, implement, and evaluate a machine learning algorithm-based Hepatitis C Emergency Department (HepC-EnD) screening tool for use in emergency departments (EDs) to identify patients at high risk of hepatitis C virus (HCV) infection. HepC-EnD will be integrated into the University of Florida Health electronic health record (EHR) system as a best practice alert (BPA) pop-up for ED providers, notifying them of patients at high risk for HCV infection and recommending both HCV and human immunodeficiency virus (HIV) screening. Investigators aim to enhance the screening and diagnosis of individuals who may otherwise remain undiagnosed and untreated. The implementation outcomes (e.g., usability) and effectiveness outcomes (e.g., HCV screening and diagnosis rates) of HepC-EnD targeted screening will be compared with universal screening (FOCUS) and conventional physician-initiated screening programs in EDs.

Key facts

Study ID
NCT07406490
Run by
University of Florida
People needed
6466
Starts
2026-07-01
Expected to finish
2027-07-01
Last updated by the study team
2026-04-29

Who can join

Age: 18 and older, up to 79. Sex: any. Healthy volunteers: accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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