High-risk Influenza Vaccine Alert

Overview

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.

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).

Conditions

Interventions

Eligibility

Locations (1)

Outcomes