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.
18-79 years of age
< 18 years of age
Medically unstable
Patients visiting UF Health emergency departments.
Cohort
Prospective
Physician-Initiated Screening (Conventional Screening)
Other interventionScreening for HCV and HIV in patients presenting to the ED occurs when an ED provider initiates screening based on symptoms or clinical judgement. Providers will manually order individual tests in the EHR.
FOCUS (Universal Screening)
Other interventionDuring nurse triage, a FOCUS screening question will appear in the EHR and the patient will be asked to opt-in to HCV and HIV testing. For those who consented, if an ED provider enters a phlebotomy order for any reason in the EHR, a BPA will alert the providers to suggest HCV and HIV testing. The provider can decide to "order" or "do not order" for each test individually. Ordered tests automatically trigger the following in the EHR: HCV antibody with reflex to RNA and HIV 1/2 antigen/antibody with reflex to confirmation. For all patients who received positive test result in the ED, standardized linkage-to-care processes will be performed. These procedures are currently implemented in clinical practice.
HepC-EnD (Targeted Screening)
Other interventionHepC-EnD will run in real time once integrated into the hospital's Epic EHR system. When the patient comes to the ED waiting room, a risk score generated from HepC-EnD will be available and determine if the patient is at high risk of HCV infection (\> cutoff risk score). If the patient is determined to be at high risk, a HepC-EnD screening question will appear in the EHR during nurse triage and the patient will be asked will be asked to opt-in to HCV and HIV testing. For those who consented, a BPA will alert the ED provider to suggest HCV and HIV testing. The provider can decide to "order" or "do not order" for each test individually. Ordered tests automatically trigger the following in the EHR: HCV antibody with reflex to RNA and HIV 1/2 antigen/antibody with reflex to confirmation. For all patients who received positive test result in the ED, standardized linkage-to-care processes will be performed.
Proportion of new HCV or HIV diagnoses
Proportion of positive results among performed tests. HCV diagnosis is defined as a positive RNA test result. HIV diagnosis is defined as an acute (i.e., antigen positive but antibody negative) or established (i.e., antibody positive) infection.
Absolute number of new HCV or HIV diagnoses
Absolute number of positive results among performed tests. HCV diagnosis is defined as a positive RNA test result. HIV diagnosis is defined as an acute (i.e., antigen positive but antibody negative) or established (i.e., antibody positive) infection.
Proportion of BPA alerts among individuals presenting to EDs
BPA alert for HepC-End or universal screening
Proportion of HCV and HIV tests performed among BPA alerts
Proportion of patients linked to care among those with positive HCV and HIV diagnoses
Linkage to care will be defined as a patient attending a first medical appointment within 3 months of receiving an HCV or HIV diagnosis.
Composite HCV or HIV Diagnoses
All HCV and HIV diagnoses will be considered separately and will include both new and repeat diagnoses.
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University of Florida
Lead sponsor
National Institute on Drug Abuse (NIDA)
Collaborator
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