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

Study Overview
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Brief Summary
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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.

Detailed Description
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Almost everyone age 6 months or older can benefit from the vaccine, which can reduce illnesses, missed work, hospitalizations, and death by reducing the likelihood of contracting influenza. Flu shots are particularly important for patients at high risk of experiencing severe outcomes. In the 2020-21 and 2021-22 flu seasons, the study team sent messages to Geisinger patients in the top 10% of risk for flu and complications according to an artificial intelligence algorithm. Messages that disclosed patients' risk status significantly increased flu vaccination rates. Additionally, messages that included risk information were most effective in patients at relatively lower risk (those in the top 4-10%) compared with those at the highest risk (top 3%). The present work will test the effectiveness of high-risk messages in patients who are in the top 11-20% of risk, at high risk but lower than previous studies. These communications will inform patients 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, or (c) the additional explanation that an AI or ML algorithm made this determination.

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

Conditions
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Influenza, Vaccination, Health Promotion, Health Behavior, Risk Reduction

Intervention / Treatment
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* Behavioral: Risk Reduction


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: 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 Exclusion criteria: - 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

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Prevention
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Single


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| No Intervention: Passive control<br>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. | |
| Experimental: Active control<br>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<br>* Letter, patient portal, SMS and/or another modality<br>|
| Experimental: High risk only<br>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<br>* Letter, patient portal, SMS and/or another modality<br>|
| Experimental: Risk based on medical records<br>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<br>* Letter, patient portal, SMS and/or another modality<br>|
| Experimental: High risk based on algorithm<br>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<br>* Letter, patient portal, SMS and/or another modality<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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 | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Flu Vaccine, Choice Architecture, Machine Learning, Perceived Credibility