Patient Portal Flu Vaccine Reminders (RCT 6)

Improving Influenza Vaccination Delivery Across a Health System by the Electronic Health Records Patient Portal RCT 6

This trial is taking place in Los Angeles, CA at 21 clinics within the UCLA Health System. The study design is a 3 arm randomized trial. Patients will be randomized into 1) receiving portal based reminder messages with a video from their PCP encouraging them to receive the influenza vaccine, 2) portal-based reminder messages with an infographic with the image of their PCP encouraging them to receive the influenza vaccine, or 3) the control group. Patients randomized to the intervention arms will receive reminders if they are due for influenza vaccine. Despite the Advisory Committee on Immunization Practices (ACIP) recommendation in 2010 that all people above 6 months of age should receive an annual flu vaccine, vaccination rates remain low: at 6m-4.9 yrs. (70%), 5-17.9 yrs. (56%), 18-64.9 yrs. (38%), and >65 yrs. (63%). The investigators will assess the effectiveness of MyChart R/R video messages and infographic messages as compared to the standard of care control (Health system messages).

Sub-optimal vaccination rates are a significant problem in the U.S., despite their effectiveness in preventing morbidity and mortality from vaccine-preventable illness. For influenza specifically, annual epidemics of influenza cause substantial morbidity in the U.S. with up to 40,00-80,000 deaths/year and many hospitalizations, emergency and outpatient visits, and significant costs. Reminder/recall (R/R), sent by phone, mail or other modality, can improve child and adult influenza vaccination rates. However, the majority of pediatric or adult primary care practices do not conduct R/R. Barriers are lack of finances, personnel, and algorithms to identify eligible patients. A technological breakthrough that might overcome these barriers involves patient portals-- secure, web-based communication systems, embedded within electronic health records (EHRs), for patients and providers to communicate with each other via email and the internet. Portals are used by about half of Americans and half of UCLA patients. Another is text messaging at the health system level. This randomized controlled trial will assess the effectiveness of reminders messages sent to portal users, encouraging influenza vaccination, on increasing influenza vaccination rates within a health system. Patients will be randomized into three groups: 1) one-third of patients will receive reminder messages with a video from their PCP encouraging them to receive the influenza vaccine, 2) one-third will receive reminders with an infographic with information about the influenza vaccine with an image of their PCP, and 3) one-third will receive standard health system messages (standard of care). Portal-based video messages: Clinicians have been shown to be trusted by their patients, so by sending patients videos that have been recorded by their own primary care physician, we are testing the concept of 'trusted messengers' to improve influenza vaccine uptake. Portal-based infographic messages: This study arm is also testing the concept of 'trusted messenger' since all infographic messages will also have an image of patients' own primary care physician at the top. Interventions that apply Behavioral Economics principles in vaccine promotion messaging can increase vaccine receipt. In the physician videos and infographics we will also include language utilizing the concepts endorsing social norms, social good, positive framing, urgency, and planning. For the primary analysis, the primary outcome will be the patient's end of flu season vaccination status. Intervention effects will be assessed using mixed effects log-binomial models. The portal-based reminder messages will be sent in October of 2023. Repeat messages will also be sent in late October, and late November to patients who do not receive their influenza vaccines.

Reminder Recall (R/R), Influenza Vaccine, Electronic Health Record, Vaccine, Video Messages, Trusted Messenger

Participants in their arm will receive up to 3 portal-based messages with a video recorded message from their own primary care physician encouraging them to receive the influenza vaccine.

Participants in their arm will receive up to 3 portal-based messages with an infographic message with an image of their own primary care physician encouraging them to receive the influenza vaccine.

Participants in this arm will only receive standard-of-care health system portal messages, and will not receive study-based messages.

Video recorded by physician encouraging patients to receive influenza vaccine. Sent via the patient portal.

Infographic with information about the influenza vaccine and an image of the physician. Sent via the patient portal.

Percent of patients with annual influenza vaccination (between 10/4/23 - 4/1/24) among adult index patients. Outcomes will be assessed via vaccine data extraction from the electronic health record and external claims and pharmacy data. The index patients must also be an active UCLA Health MyChart user (>= 1 login over the last 12 months from 8/1/23, excluding activity on the user's initial profile activation date). Individuals not affiliated with any primary care practice will be excluded from the primary analysis.

Percent of patients with annual influenza vaccination (between 10/4/23 - 4/1/24) among pediatric index patients. Outcomes will be assessed via vaccine data extraction from the electronic health record and external claims and pharmacy data. The index patients must also be an active UCLA Health MyChart user (>= 1 login over the last 12 months from 8/1/23, excluding activity on the user's initial profile activation date). Individuals not affiliated with any primary care practice will be excluded from the primary analysis.

Inclusion Criteria: - Active Portal Users A patient within the UCLA Health System identified as a primary care patient per an internal algorithm Exclusion Criteria: - A patient within the UCLA Health System not identified as a primary care patient per an internal algorithm