Document Type

Master's Culminating Experience

Publication Date



A network simulation was applied to hospital social networks improve the influenza vaccination rate of healthcare workers in a healthcare system. Social network methods can be used to develop an understanding of structures of social relations. Over 200,000 U.S. patients are hospitalized annually for influenza, which attributes to 36,000 deaths and is the sixth leading cause of death in adults. The best way to prevent influenza each year is by receiving the influenza vaccination. The typical influenza vaccination rate among healthcare workers is 40- 50%. A Healthy People 2020 objective is to increase the percentage of healthcare workers who are vaccinated annually against influenza from 45.5% in 2008 to 90%. This simulation used hypothetical questionnaire results regarding demographic, vaccination status and network focused data. Pajet Matrix Maker and NodeXL were used to analyze and create a visual representation of the hypothetical data. Our resulting sociogram illustrated that some nodes were very influential with many ties and some nodes had few ties. Complexity can be used to analyze and measure a network. The study of complexity can advise health officials to use nonlinear models, accept unpredictability, and respond to emerging patterns. The Social Network Theory, Health Belief Model, and Diffusion of Innovation were used to approach the study of influenza vaccination strategies. Previous studies focus on social network methodologies, but omit the application of social networks on real world situations. The core ideas of social network analysis have potential to enrich our understanding of fields outside the social sciences.

Additional Files

Attenweiler_Thomure_poster.pdf (333 kB)