At a glance
ClinicalIndex Comparison RecordStandardized by ClinicalIndex from the ClinicalTrials.gov record · verify against the source.
Encouraging Flu Vaccination Among High-Risk Patients Identified by a Machine-Learning Model of Flu Complication Risk
In Brief
A clinical study evaluating Risk reduction, Medical records-based recommendation, and 1 other intervention for Influenza and 4 related conditions. Completed, enrolled 117,649 participants across 1 site.
Detailed Summary
The purpose of the current study is to test different interventions to determine the most effective way to promote flu vaccine uptake in a high-risk population identified by an "artificial intelligence" (AI) or machine learning (ML) algorithm. The specific aims are: 1. Evaluate the effect on flu vaccination rates of informing health-system patients who are identified by an ML analysis of EHR data to be at high risk for flu complications that they are at high risk with either (a) no additional explanation, (b) an explanation that this determination comes from an analysis of their medical records, and (c) the additional explanation that an AI or ML algorithm made this determination. 2. Evaluate the effects of the same three interventions on diagnoses of flu in the same patients.
Study Details
Timeline
Interventions
Mailed letter, SMS, and/or patient portal message
Mailed letter, SMS, and/or patient portal message
Mailed letter, SMS, and/or patient portal message