Statistical Methods for Visualizing Healthcare Big Data

Abstract

With the advancement and acceleration of digital technology, the demand and supply of healthcare big data are increasing. In Korea, the government and companies have made various efforts to utilize healthcare big data, such as deregulation data-related legal regulations and data linkage between different institutions. As a result, many researchers have been able to access a variety of healthcare big data. Although healthcare big data has a vast amount and high value, many researchers are unable to fully access healthcare big data because there are difficulties in processing, analysis, and interpretation for data. The data visualization is recognized as an important tool that can solve these limitations. Using data visualization, researchers can intuitively understand complex data and receive support for decision-making. Additionally, these visualizations promote effective communication between experts in different fields and between experts and non-experts. Visualization is used in a variety of research fields and processes, including data summarization, data exploration, and evaluation and interpretation of predictive models. Various types of visualization have different meanings depending on how they are expressed. Therefore, it is important to express the meaning of visualization appropriately. This study provides representative examples of visual representations for data summarization, data exploration, and predictive model evaluation. This study aimed to improve easier access and utilization of healthcare big data by providing R code and visualization results.