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Clinical Trial Summary

This study will test the relative efficacy of high-risk messages in increasing flu shot rates in patients at moderately high risk for flu and complications (those in the top 11-20% of risk). It will also examine whether informing patients that their high-risk status was determined by analyzing their medical records or by an artificial intelligence (AI) / machine-learning (ML) algorithm analyzing their medical records will affect the likelihood of receiving a flu vaccine.


Clinical Trial Description

Almost everyone age 6 months or older can benefit from the vaccine, which can reduce illnesses, missed work, hospitalizations, and death by reducing the likelihood of contracting influenza. Flu shots are particularly important for patients at high risk of experiencing severe outcomes. In the 2020-21 and 2021-22 flu seasons, the study team sent messages to Geisinger patients in the top 10% of risk for flu and complications according to an artificial intelligence algorithm. Messages that disclosed patients' risk status significantly increased flu vaccination rates. Additionally, messages that included risk information were most effective in patients at relatively lower risk (those in the top 4-10%) compared with those at the highest risk (top 3%). The present work will test the effectiveness of high-risk messages in patients who are in the top 11-20% of risk, at high risk but lower than previous studies. These communications will inform patients they are at high risk with either (a) no additional explanation, (b) an explanation that this determination comes from an analysis of their medical records, or (c) the additional explanation that an AI or ML algorithm made this determination. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05509283
Study type Interventional
Source Geisinger Clinic
Contact
Status Completed
Phase N/A
Start date September 13, 2022
Completion date October 26, 2022

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