Clinical trial NCT05492786: High-risk Influenza Vaccine Alert
Official title: Alerts With Risk Information to Increase Influenza Vaccinations
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Influenza
Keywords: Vaccination
Health Promotion
Health Behavior
Reminder Systems
Economics, Behavioral
Risk Assessment
Lead sponsor: Geisinger Clinic
Sponsor class: OTHER
Collaborators: name: Massachusetts Institute of Technology
name: National Institute on Aging (NIA)
name: National Bureau of Economic Research, Inc.
First posted: 2022-08-09
Enrollment: 80452
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 assess, prospectively, the effect on flu vaccination rates of salient alerts in the electronic health record that indicate a patient's high risk for flu and its complications. The investigators hypothesize that the salient alerts will lead to increased flu vaccination compared with a standard flu alert.

Detailed description: The CDC (Centers for Disease Control) 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. One barrier to vaccination is a lack of "cues to action," and, in particular, the lack of direct recommendation from medical personnel; this barrier is arguably the most effectively overcome by a simple nudge of clinicians, compared with barriers such as negative attitudes toward vaccination, low perceived utility of vaccination, and less experience with having received the vaccine.

Geisinger partnered with Medial EarlySign (Medial) to develop a machine learning (ML) algorithm to help identify people at risk for serious flu-associated complications based on existing electronic health record data. Eligible at-risk patients will be randomized to an active control group (clinician will be shown a standard flu alert) or one of two experimental groups (clinician will be shown an alert indicating patient's high risk, with or without describing the patient's factors contributing to that risk).

Eligibility criteria: Patient Inclusion Criteria:

* Age 18+
* Have been determined to be in the top 20% of risk through Medial's ML algorithm
* Attend an appointment where the flu alert fires (Geisinger sets when flu alerts start and end--between \~9/1/2022 and \~4/30/2023, as well as the trigger conditions for the alert, which includes valid departments and visits and excludes contraindications like Guillain-Barre syndrome)

Clinician Inclusion Criteria:

* Any Geisinger clinician who sees patient-participants in our study for an appointment where their flu shot alert fires

Primary outcomes:
measure: Flu Vaccination
timeFrame: At the 1 day visit
Secondary outcomes:
Other outcomes:
measure: High Confidence Flu Diagnosis
timeFrame: Up to 8 months
measure: "Likely Flu" Diagnosis
timeFrame: Up to 8 months
measure: Flu Complications
timeFrame: Up to 8 months
measure: ER Visits
timeFrame: Up to 11 months
measure: Hospitalizations
timeFrame: Up to 11 months
measure: COVID-19 Vaccination Rates
timeFrame: Up to 8 months
measure: Flu Vaccination During the 2022-2023 Season
timeFrame: Up to 8 months
measure: Flu Vaccination by Sex
timeFrame: At the 1 day visit
measure: Flu Vaccination by Race
timeFrame: At the 1 day visit
measure: Flu Vaccination by Ethnicity
timeFrame: At the 1 day visit
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: