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Completed

NCT Number: NCT05509283

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

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.

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Key information

Conditions

Influenza Behavior Health Behavior Health Promotion Infections Influenza, Human Orthomyxoviridae Infections RNA Virus Infections Respiratory Tract Diseases Respiratory Tract Infections Risk Reduction Risk Reduction Behavior Vaccination Virus Diseases

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Geisinger

Danville, Pennsylvania, 17822, United States

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Risk reduction

Behavioral

Letter, patient portal, SMS and/or another modality

Primary outcomes

  1. Flu vaccination

    Time frame: Within 6 weeks of the patient's study start date

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

Other outcomes

  1. High confidence flu diagnosis

    Time frame: Up to 8 months

    Patient received a flu diagnosis via a positive polymerase chain reaction (PCR)/antigen/molecular test (yes/no) during the 2022-23 flu season (from the patient's study start date through April 30, 2023).

  2. "Likely flu" diagnosis

    Time frame: Up to 8 months

    Received a "high confidence flu" diagnosis (with positive PCR/antigen/molecular test) and/or "likely flu" diagnosis (as assessed via International Classification of Disease [ICD] codes or Tamiflu administration or positive PCR/antigen/molecular test) (yes/no) during the 2022-23 flu season (from the patient's study start date through April 30, 2023).

    Note that "likely flu" is a superset of the "high confidence flu" diagnoses.

  3. Flu complications

    Time frame: Up to 11 months

    Diagnosed with flu-related complications (yes/no) from the patient's study start date through July 31, 2023.

  4. ER visits

    Time frame: Up to 11 months

    Number of ER visits from the patient's study start date through July 31, 2023.

  5. Hospitalizations

    Time frame: Up to 11 months

    Number of hospitalizations from the patient's study start date through July 31, 2023.

  6. COVID-19 vaccination rates

    Time frame: Up to 8 months

    Received at least one COVID-19 vaccination (yes/no) during the 2022-23 flu season (from the patient's study start date through April 30, 2023).

Sponsors and collaborators

Lead sponsor

Geisinger Clinic

Other

Collaborators

  • Massachusetts Institute of Technology
  • National Bureau of Economic Research, Inc.

Registry information

Important dates

Study start
2022
Primary completion
2022
Study completion
2022
First posted
Aug 22, 2022
Registry last updated
Dec 5, 2022

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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