High-risk Influenza Vaccine Alert

Geisinger Health

Status: Completed

Conditions: Influenza

Treatments: Behavioral: Alert; Behavioral: High-risk Text; Behavioral: Salient alert features; Behavioral: Risk factors

Study type: Interventional

Funder types: Other; NIH

Identifiers

NCT05492786

P30AG034532 (U.S. NIH Grant/Contract)

2022-0502

Details and patient eligibility

About

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.

Full 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).

Enrollment: 80,452 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion and exclusion 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

Trial design

Primary purpose: Prevention

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Single Blind

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80,452 participants in 3 patient groups

Standard Alert

Active Comparator group

Description:

Standard flu alert

Treatment:

Behavioral: Alert

High-risk Alert

Experimental group

Description:

Flu alert that indicates patient is at high risk for flu and its complications

Treatment:

Behavioral: Salient alert features

Behavioral: High-risk Text

Behavioral: Alert

High-risk Alert with Risk Factors

Experimental group

Description:

Flu alert that indicates patient is at high risk for flu and its complications and presents the factors contributing to this high risk

Treatment:

Behavioral: Risk factors

Behavioral: Salient alert features

Behavioral: High-risk Text

Behavioral: Alert