DATA ANALYTICS AND VISUALIZATION FOR VIRTUAL SIMULATION
- Project Research
- 1-5 Chapters
- Abstract : Available
- Table of Content: Available
- Reference Style: APA
- Recommended for : Student Researchers
- NGN 3000
ABSTRACT
Data Analytics and Visualization for Virtual Simulation. Healthcare organizations attract a diversity of caregivers and patients by providing essential care. While interacting with people of various races, ethnicity, and economical background, caregivers need to be empathetic and compassionate. Proper training and exposure are needed to understand the patient’s background and handle different situations and provide the best care for the patient. With social determinants of health (SDOH) as the basis, the thesis focuses on providing exposure through “Wright LIFE (Lifelike Immersion for Equity) - A simulation-based training tool” to two such scenarios covering patients from the LGBTQIA+ community & autism spectrum disorder (ASD). This interactive tool helps to create mindfulness about the social and economic disparities faced by the patients through realistic and captivating gameplay. Though the primary focus of the “Wright LIFE” application is “Digital Learning”, it would help to understand how effective the application is in terms of improving the provider's abilities. Through statistical evidence, the tool can be improved, which in turn will improve the user experience. For this analysis, during the simulation, we also focus on collecting the data gathered from the participants through surveys. The simulation includes different questionnaires where participants can provide feedback at various stages within the simulation. This then allows for a comparison between the participants’ responses to see the rate of improvement as a result of the simulation. To analyze the data from the iv participant's responses, data analysis, and visualization tools help to represent the data using charts, infographics, animations, and many more to assist this in this analytic process. The analysis of the data can help to understand the trend of the participants’ responses to the questionnaire. The goal of the questionnaire is to collect participants’ responses to assess anxiety, frustration, and compassion levels pre- and post-simulation. A comparative analysis is then performed. This analysis shows that the provider’s anxiety and frustration decreased after the simulation whereas the compassion increased. This is an indication that the simulation can improve the provider’s experience while working with patients with biases. The data also helped to identify the users who actively participated in the survey based on demographic data like gender, profession, experience, and age. “A picture is worth a thousand words”. Through visualization, we can bring the data to life and provide a clear idea of what the data represents by giving visual context. Tableau is used for visualizing the survey data collected from the “SDOH” simulation consisting of responses from the providers before and after the interaction with the patients. The visualizations transform the raw data into simple and informative graphs to understand the behavioral trends and to check how the providers respond to the stories in the simulations. This allows us to determine the effectiveness of the simulation more efficiently.
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