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Efficacy of Communication Modalities for Promoting Flu Shots

Not Applicable
Completed
Conditions
Health Promotion
Risk Reduction
Influenza Vaccination
Health Behavior
Interventions
Behavioral: Letter
Behavioral: SMS
Behavioral: Patient portal
Registration Number
NCT05509270
Lead Sponsor
Geisinger Clinic
Brief Summary

The purpose of this study is to test which modalities (mailed letter, short message service \[SMS\] text, or patient portal messages) are most effective for encouraging flu shots in high-risk patients.

Detailed Description

The Centers for Disease Control (CDC) recommends a flu vaccination to everyone aged 6+ months, with rare exception; almost anyone can benefit from the vaccine, which can reduce illnesses, missed work, hospitalizations, and death. Flu shots are particularly important for patients at high risk of experiencing severe outcomes.

During 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 told patients they were at high risk significantly increased their likelihood of getting vaccinated.

The present study will extend previous work by testing which modality or modalities are most effective at boosting flu shot rates in patients at high risk. In previous campaigns, patients received messages via all communication modalities patients were eligible for (mailed letter, SMS text, and/or patient portal message). In this study, patients will be randomized to receive high-risk messages in one or more modalities.

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
43225
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 10% 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

Study & Design

Study Type
INTERVENTIONAL
Study Design
PARALLEL
Arm && Interventions
GroupInterventionDescription
Letter onlyLetterThis group will receive a letter telling them they are at high risk for flu and complications
SMS onlySMSThis group will receive an SMS telling them they are at high risk for flu and complications
Patient portal + SMSSMSThis group will receive a patient portal message and an SMS telling them they are at high risk for flu and complications
Letter + Patient portal + SMSLetterThis group will receive a letter, a patient portal message, and an SMS telling them they are at high risk for flu and complications
Letter + Patient portal + SMSPatient portalThis group will receive a letter, a patient portal message, and an SMS telling them they are at high risk for flu and complications
Letter + Patient portal + SMSSMSThis group will receive a letter, a patient portal message, and an SMS telling them they are at high risk for flu and complications
Patient portal onlyPatient portalThis group will receive a patient portal message telling them they are at high risk for flu and complications
Patient portal + SMSPatient portalThis group will receive a patient portal message and an SMS telling them they are at high risk for flu and complications
Primary Outcome Measures
NameTimeMethod
Flu vaccination4 weeks after the first messages are sent in the study

Flu vaccination within 4 weeks of the first message send date

Secondary Outcome Measures
NameTimeMethod

Trial Locations

Locations (1)

Geisinger

🇺🇸

Danville, Pennsylvania, United States

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