Clinical trial NCT06566534: Personalized Nudging to Increase Influenza Vaccinations
Official title: A Prospective Randomized Trial of Personalized Nudges to Increase Influenza Vaccinations
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Influenza, Human
Keywords: vaccination
health promotion
health behavior
reminder systems
behavioral economics
behavioral risk assessment
machine learning
personalization
nudges
Lead sponsor: Geisinger Clinic
Sponsor class: OTHER
Collaborators: name: Massachusetts Institute of Technology
name: University of Michigan
name: Abdul Latif Jameel Poverty Action Lab
First posted: 2024-08-22
Enrollment: 77482
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: PREVENTION

Brief summary: The purpose of this study is to prospectively test whether personalized, message-based nudges can increase flu vaccination compared with nudges that are not personalized or no nudges.

Detailed description: On average, 8% of the US population gets sick from influenza each flu season. Since 2010, the annual disease burden of influenza in the U.S. has included 9-41 million illnesses, 140,000-710,000 hospitalizations, and 12,000-52,000 deaths. The Centers for Disease Control and Prevention (CDC) recommends flu vaccination to everyone aged 6 months and older, with rare exceptions; almost anyone can benefit from the vaccine, which can reduce illnesses, missed work, hospitalizations, and death.

Successful efforts to get patients vaccinated against influenza have included text message reminders timed to precede upcoming flu shot-eligible appointments by up to 3 days. For example, the Roybal-funded flu shot megastudy conducted with Penn Medicine and Geisinger patients assessed the effectiveness of numerous types of messages in increasing vaccination, relative to standard communications by the respective health systems; an average 2.1 percentage point absolute increase (or 5% relative increase) in flu shots occurred due to the messages. Similarly, follow-up analysis of the megastudy using machine learning revealed that interventions differed in relative effectiveness across groups of patients as a function of overlapping covariates (e.g., age, sex, insurance type, and comorbidities). This analysis found that nudges optimally targeted to subgroups who responded most strongly to those nudges in the megastudy would have resulted in up to three times the increases in vaccination observed when simply randomly assigning patients to messages.

The present study aims to prospectively test the efficacy of a patient-facing, message-based nudge via short message service (SMS) texts that is predicted by this retrospective machine learning algorithm to be most effective for them (Personalized Nudge) relative to Passive Control (no messages), Active Control (simple reminder message), and Best Nudge (best performing message from the 2020 megastudy). Patients will be randomized to one of these four arms.

Of the 19 original messages from the megastudy, 12 can be carried out at Geisinger in 2024; the other 7 are either no longer relevant (e.g., those that refer to an ongoing coronavirus pandemic) or cannot be carried out due to a technical limitation (e.g., Geisinger is unable to send pictures, so nudges with pictures are excluded). A treatment assignment tree based on the algorithm described above will be applied to this subset of nudges to generate rules for assigning patients to personalized messages based on observed covariates.

The last patients will be enrolled on December 28th for appointments scheduled on December 31st. At least 90,000 patients are expected to be enrolled.

Eligibility criteria: Inclusion Criteria:

* Age 18+
* Has not received the 2024 flu vaccine according to the Geisinger electronic health record (EHR) prior to randomization
* Has a non-acute, flu-shot eligible, in-person Geisinger appointment scheduled with enough time to be randomized
* Has a Geisinger primary care provider

Exclusion Criteria:

* Cannot be contacted by SMS (e.g., due to insufficient/missing contact information in the EHR or because they opted out)
* Appointment type or department not approved for outreach by Geisinger leadership at the time of outreach
* Has an allergy to flu vaccines according to any EHR allergy table known to the study team
* Has a health maintenance modifier indicating they are permanently discontinued from receiving a seasonal flu shot
* Shares a phone number with someone who has already been enrolled

Primary outcomes:
measure: Number of Patients With Flu Shot Receipt Between Enrollment Date and Target Appointment Date
timeFrame: Between the enrollment date and target appointment date (at least 4 days and up to 4 months)
Secondary outcomes:
Other outcomes:
measure: Number of Patients With Flu Shot Receipt On or Before December 31, 2024
timeFrame: Up to 4 months after randomization
measure: Number of Patients with Flu Shot Receipt Between Enrollment Date and First Eligible Appointment
timeFrame: 4 Days
measure: Number of Patients with Flu Diagnosis (encounter diagnosis or flu test)
timeFrame: Up to 8 months after randomization
measure: Number of Patients with Flu-related Complications
timeFrame: Up to 11 months after randomization
Locations:
city: Danville
country: United States
facility: Geisinger Clinic
state: Pennsylvania
Study officials:
affiliation: Geisinger Clinic
name: Christopher F Chabris, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Milkman KL, Patel MS, Gandhi L, Graci HN, Gromet DM, Ho H, Kay JS, Lee TW, Akinola M, Beshears J, Bogard JE, Buttenheim A, Chabris CF, Chapman GB, Choi JJ, Dai H, Fox CR, Goren A, Hilchey MD, Hmurovic J, John LK, Karlan D, Kim M, Laibson D, Lamberton C, Madrian BC, Meyer MN, Modanu M, Nam J, Rogers T, Rondina R, Saccardo S, Shermohammed M, Soman D, Sparks J, Warren C, Weber M, Berman R, Evans CN, Snider CK, Tsukayama E, Van den Bulte C, Volpp KG, Duckworth AL. A megastudy of text-based nudges encouraging patients to get vaccinated at an upcoming doctor's appointment. Proc Natl Acad Sci U S A. 2021 May 18;118(20):e2101165118. doi: 10.1073/pnas.2101165118.
citation: Patel MS, Milkman KL, Gandhi L, Graci HN, Gromet D, Ho H, Kay JS, Lee TW, Rothschild J, Akinola M, Beshears J, Bogard JE, Buttenheim A, Chabris C, Chapman GB, Choi JJ, Dai H, Fox CR, Goren A, Hilchey MD, Hmurovic J, John LK, Karlan D, Kim M, Laibson D, Lamberton C, Madrian BC, Meyer MN, Modanu M, Nam J, Rogers T, Rondina R, Saccardo S, Shermohammed M, Soman D, Sparks J, Warren C, Weber M, Berman R, Evans CN, Lee SH, Snider CK, Tsukayama E, Van den Bulte C, Volpp KG, Duckworth AL. A Randomized Trial of Behavioral Nudges Delivered Through Text Messages to Increase Influenza Vaccination Among Patients With an Upcoming Primary Care Visit. Am J Health Promot. 2023 Mar;37(3):324-332. doi: 10.1177/08901171221131021. Epub 2022 Oct 4.