InfluenzaNCT05509283
Nudging Flu Vaccination in Patients at Moderately High Risk for Flu and Flu-related Complications
A study testing Risk Reduction in people with Influenza and Vaccination, run by Geisinger Clinic at 1 site in United States.
Trial 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). Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Influenza, Vaccination, Health Promotion
- What is being tested?
- Risk Reduction
- Type of treatment
- Vaccines, Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 40,671 participants
- Where
- 1 siteUnited States
- Study dates
- 13 Sep 2022to 26 Oct 2022
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country.
About this study
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.
Read the detailed description
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.
- Conditions
- Influenza, Vaccination, Health Promotion, Health Behavior, Risk Reduction
- Being tested
- Risk Reduction
- Keywords
- Flu Vaccine, Choice Architecture, Machine Learning, Perceived Credibility
- Medical subject headings
- Influenza, Human, Health Behavior, Risk Reduction Behavior
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Risk ReductionBehavioural
Letter, patient portal, SMS and/or another modality
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: 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. Receives: 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. Receives: 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. Receives: Behavioral: Risk Reduction |
What is being measured
The primary outcome is the main question the study is designed to answer.
Flu vaccination
Received a flu vaccination within within 6 weeks of the patient's study start date
Measured: Within 6 weeks of the patient's study start date
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Aug 2022
- Study start13 Sep 2022
- Primary completion26 Oct 2022
- Study completion26 Oct 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for InfluenzaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Care provider
- Enrolment
- 40,671 participants (actual)
Sponsor and investigators
- Lead sponsor
- Geisinger Clinic
- Sponsor type
- University, hospital or other
- Collaborators
- National Bureau of Economic Research, Inc., Massachusetts Institute of Technology
- Responsible party
- Principal investigator, Christopher F Chabris, PhD, Geisinger Clinic
- Investigators
- Christopher Chabris, PhD, Principal investigator, Geisinger Clinic
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05509283
- Sponsor's protocol ID
- 2022-0410
- Status last verified
- Dec 2022
- First submitted
- 18 Aug 2022
- Last updated
- 5 Dec 2022
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Data with no personally identifiable information will be made available to other researchers on the Open Science Framework for transparency. This will include the essential data and code needed to replicate the analysis that yielded reported findings.
Publications
Rosenbaum GM, Goren A, Shermohammed M, Wolk DM, Tice AM, Doyle JJ Jr, Meyer MN, Chabris CF. Algorithm-assisted personalized risk communication to encourage flu vaccination in the USA: three randomized field trials. Nat Hum Behav. 2026 Oct 5. doi: 10.1038/s41562-026-02603-4. Online ahead of print.
PubMed 42834081
Study at a glance
From the registry record, last updated by the sponsor on 5 Dec 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Nudging Flu Vaccination in Patients at Moderately High Risk for Flu and Flu-related Complications
- ClinicalTrials.gov ID
- NCT05509283
- Acronym / sponsor ID
- 2022-0410
- Conditions
- Influenza, Vaccination, Health Promotion, Health Behavior, Risk Reduction
- Keywords
- Flu Vaccine, Choice Architecture, Machine Learning, Perceived Credibility
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 40,671 participants (actual)
- Lead sponsor
- Geisinger ClinicUniversity, hospital or other
- Collaborators
- National Bureau of Economic Research, Inc., Massachusetts Institute of Technology
- Study start
- 13 Sep 2022 (actual)
- Primary completion
- 26 Oct 2022 (actual)
- Study completion
- 26 Oct 2022 (actual)
- First posted
- 22 Aug 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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
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.
Study design
- Primary purpose
- Prevention
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (care provider)
- Number of arms
- 5
| Arm | Type | Receives |
|---|---|---|
| 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 | Behavioral: Risk ReductionPatients in the active control arm will receive messages reminding them to get a flu shot without being advised of their risk status. |
| High risk only | Experimental | Behavioral: Risk ReductionPatients 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. |
| Risk based on medical records | Experimental | Behavioral: Risk ReductionPatients 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. |
| High risk based on algorithm | Experimental | Behavioral: Risk ReductionPatients 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (5 listed)
- 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
Key exclusion criteria (1 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Risk ReductionLetter, patient portal, SMS and/or another modality | Behavioural | Active control, High risk based on algorithm, High risk only, Risk based on medical records |
Primary outcome
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
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 Dec 2022.
- Derived from this study: PubMed 42834081Rosenbaum GM, Goren A, Shermohammed M, Wolk DM, Tice AM, Doyle JJ Jr, Meyer MN, Chabris CF. Algorithm-assisted personalized risk communication to encourage flu vaccination in the USA: three randomized field trials. Nat Hum Behav. 2026 Oct 5. doi: 10.1038/s41562-026-02603-4. Online ahead of print.
- Individual participant dataSharing planned: Yes. Data with no personally identifiable information will be made available to other researchers on the Open Science Framework for transparency. This will include the essential data and code needed to replicate the analysis that yielded reported findings.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Christopher Chabris, PhD principal investigator
Geisinger Clinic
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Risk Reduction in people with Influenza and Vaccination, run by Geisinger Clinic at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 5 Dec 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Flu vaccination (time frame: Within 6 weeks of the patient's study start date). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05509283, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 5 Dec 2022.