Encouraging Flu Vaccination Among High-Risk Patients Identified by a Rule-Based Additive Risk Index

While most individuals recover from influenza without complications, certain populations-including older adults and those with underlying medical conditions-are at increased risk for severe outcomes such as pneumonia, other respiratory complications, and death. Identifying these high-risk patients is therefore important for targeting outreach and improving vaccination uptake.

Over the past three influenza seasons, Geisinger has sent as standard of care messages to patients identified as high risk for flu and flu-related complications, informing them of their risk and encouraging vaccination. These messages were implemented following a series of four randomized controlled trials conducted by the study team, which demonstrated that such messages increased influenza vaccination rates (Rosenbaum et al., 2026).

Previously, high-risk patients were identified using an AI-based model. Patients were considered high risk if they were in the top 15% of risk among Geisinger patients eligible for scoring by the model. Due to logistical and resource constraints, this model is no longer available for use. As a result, an alternative, scalable approach is needed to identify high-risk patients for upcoming influenza seasons.

Recent evidence suggests that a simple count of Center for Disease Control (CDC)-defined influenza risk factors is predictive of severe influenza outcomes (McGovern et al., 2024). This approach constructs a rule-based additive risk index by summing the number of CDC-defined high-risk conditions present in each patient's electronic health record. Results indicate that this simple index is highly informative for identifying patients at increased risk of influenza-related complications.

This study will evaluate whether a rule-based additive risk index derived from Electronic Health Record (EHR) data can be used to identify patients at high risk for influenza and influenza-related complications and support targeted outreach. Specifically, the study will assess whether informing patients with four or more CDC risk factors (representing approximately the top 15% of the distribution of scores for eligible patients) of their elevated risk increases influenza vaccination uptake.