Rule-Based High-Risk Flu

NCT07798882 | Not Yet Recruiting

• 1 other identifier: 2026-0673
• Study Type: interventional
• Target: 51,215
• Locations: 1 country
• Sites: 1

Brief Summary

Previous work by the study team has shown that informing patients of their high risk of flu and flu-related complications increases their likelihood of getting a flu shot (Rosenbaum et al., 2026). In this work, an artificial intelligence (AI)-based algorithm determined which patients were at high risk for flu. This year, the team will test whether risk messages remain effective when a non-algorithmic rule-based additive risk index (McGovern et al., 2024) is used to identify patients at high risk.

Conditions

Influenza; Vaccination; Risk Reduction; Health Behavior; Health Promotion

Keywords

Flu vaccine; Choice architecture

Outcome Measures

Primary Outcomes (1)

• Flu vaccination (y/n)

  Flu vaccine documented in the electronic health record

  In the 29 days following the date the first messages were sent

Study Arms (2)

Control

NO INTERVENTION

This group will not be sent high-risk flu shot messages, but will be sent normal system messages about flu shots.

High-risk outreach

EXPERIMENTAL

This group will be sent messages informing them of their high risk for flu and flu-related complications, in addition to the normal system messages sent to the control group.

Behavioral: Risk reduction

Interventions

Risk reduction BEHAVIORAL

Mailed letter, patient portal message and/or text message

High-risk outreach

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Age 18 or older
• Has four or more CDC risk factors for influenza reflected in EHR data
• Has a primary care physician employed by Geisinger
• Attended at least one appointment at Geisinger between 7/17/2024 and 7/16/2026
• Attended at least one primary care appointment at Geisinger between 10/1/2008 and 7/16/2026
• \- Attended an appointment at Community Care between 9/1/2024 and 7/16/2026

Sponsors & Collaborators

• Geisinger Clinic: lead

Study Sites (1)

Geisinger Health

Danville, Pennsylvania, 17822, United States

Location

MeSH Terms

Conditions

Influenza, Human; Risk Reduction Behavior; Health Behavior

Interventions

Numbers Needed To Treat

Condition Hierarchy (Ancestors)

Respiratory Tract Infections; Infections; Orthomyxoviridae Infections; RNA Virus Infections; Virus Diseases; Respiratory Tract Diseases; Behavior

Intervention Hierarchy (Ancestors)

Sample Size; Research Design; Methods; Investigative Techniques

Central Study Contacts

Gail Rosenbaum, PhD

CONTACT

570-243-1199; grosenbaum@geisinger.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Masking Details: Patients will not be informed specifically of their assignment to different arms throughout the study but patients in the intervention arm will know about their messages.
• Purpose: PREVENTION
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Program Director, Behavioral Insights Team

Model Details: Patients from the high-risk sample will be randomly assigned to one of 2 groups: * Control: Not sent high-risk flu messages. * High-risk outreach: Sent high-risk flu messages if they meet criteria set by the Marketing message campaign. Both groups will be sent additional system messages about flu shots that do not mention high-risk status.

Study Record Dates

• First Submitted: August 28, 2026
• First Posted: September 2, 2026
• Study Start: September 1, 2026
• Primary Completion: September 30, 2026
• Study Completion: September 30, 2026
• Last Updated: September 2, 2026

Record last verified: 2026-08

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)