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

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.

NCT Number	NCT07406490
Lead Sponsor	University of Florida Collaborators: National Institute on Drug Abuse (NIDA)
Conditions	Hepatitis C Virus (HCV), Hepatitis C Virus (HCV) Infection, HIV (Human Immunodeficiency Virus)
Enrollment	6,466 participants
Start Date	2026-07-01
Primary Completion	2027-06-30 (estimated)
Study Completion	2027-07 (estimated)
Updated on ClinicalTrials.gov	2026-04-29