Nudging Flu Vaccination in Patients at Moderately High Risk for Flu and Flu-related Complications

NCT05509283 | Completed DMC

• 1 other identifier: 2022-0410
• Study Type: interventional
• Target: 40,671
• Locations: 1 country
• Sites: 1

Brief Summary

This study will test the relative efficacy of high-risk messages in increasing flu shot rates in patients at moderately high risk for flu and complications (those in the top 11-20% of risk). It will also examine whether informing patients that their high-risk status was determined by analyzing their medical records or by an artificial intelligence (AI) / machine-learning (ML) algorithm analyzing their medical records will affect the likelihood of receiving a flu vaccine.

Conditions

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

Keywords

Flu Vaccine; Choice Architecture; Machine Learning; Perceived Credibility

Outcome Measures

Primary Outcomes (1)

• Flu vaccination

  Received a flu vaccination within within 6 weeks of the patient's study start date

  Within 6 weeks of the patient's study start date

Other Outcomes (6)

• High confidence flu diagnosis

  Up to 8 months

• "Likely flu" diagnosis

  Up to 8 months

• Flu complications

  Up to 11 months

Study Arms (5)

Passive control

NO INTERVENTION

Patients in the passive control arm will receive no additional pro-vaccination intervention beyond the health system's normal efforts. Although some patients are currently targeted for flu vaccination encouragement due to a conventional non-ML assessment that they are at high risk for complications, these patients are not told that they are at high risk or that they have been targeted.

Active control

EXPERIMENTAL

Patients in the active control arm will receive messages reminding them to get a flu shot without being advised of their risk status.

Behavioral: Risk Reduction

High risk only

EXPERIMENTAL

Patients in this treatment arm will receive messages telling them they have been identified to be at high risk for flu complications, without specifying how or why the health system believes this to be the case.

Behavioral: Risk Reduction

Risk based on medical records

EXPERIMENTAL

Patients in this treatment arm will receive messages telling them they have been identified to be at high risk for flu complications via review of their medical records.

Behavioral: Risk Reduction

High risk based on algorithm

EXPERIMENTAL

Patients in this treatment arm will receive messages telling them they have been identified to be at high risk for flu complications via analysis of their medical records by a computer algorithm.

Behavioral: Risk Reduction

Interventions

Risk Reduction BEHAVIORAL

Letter, patient portal, SMS and/or another modality

Active control; High risk based on algorithm; High risk only; Risk based on medical records

Eligibility Criteria

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

You may qualify if:

• Included on a list of active Geisinger patients (all patients on this list attended at least one primary care appointment at Geisinger between 10/1/2008 and 4/13/2022, and either had a Geisinger primary care provider assigned as of April 2022, or were in the Electronic Health Record \[EHR\] since at least September 2021 and had at least one encounter in 2020-2022)
• Aged 18 or older
• In the top 11-20% of risk for flu and flu complications, according to Medial's flu complications machine learning algorithm (which operates on coded EHR data)
• Has a Geisinger PCP assigned as of August 2022
• Has had an encounter in the last 2 years as of August 2022

You may not qualify if:

• \- Cannot be contacted via any of the communication modalities (e.g., letter, patient portal, SMS) being used in the study, either due to insufficient/missing contact information in the EHR or because they opted out of all modalities

Sponsors & Collaborators

• Geisinger Clinic: lead
• National Bureau of Economic Research, Inc.: collaborator
• Massachusetts Institute of Technology: collaborator

Study Sites (1)

Geisinger

Danville, Pennsylvania, 17822, United States

Location

MeSH Terms

Conditions

Influenza, Human; Health Behavior; Risk Reduction 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

Study Officials

• Christopher Chabris, PhD

  Geisinger Clinic

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: CARE PROVIDER
• Masking Details: Providers who prescribe vaccination and diagnose conditions will not be randomized to study arms or informed of patient assignment. Although patients will not be explicitly informed which arm they have been randomized to, they will be aware of the messages they receive.
• Purpose: PREVENTION
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: August 18, 2022
• First Posted: August 22, 2022
• Study Start: September 13, 2022
• Primary Completion: October 26, 2022
• Study Completion: October 26, 2022
• Last Updated: December 5, 2022

Record last verified: 2022-12

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL
• Time Frame: The data will become available after publication of study results in a scientific journal and will be available as long as the Open Science Framework hosts the data.
• Access Criteria: The data on the Open Science Framework will be open to anyone requesting that information.

Locations

US (1)