A Study on How to Link, Integrate, Utilize Multi-Source Data to Vitalize the Data Economy in the Health and Welfare

Abstract

In line with the data open trend, a large amount of data is being opened. However, they are individually distributed and provided so that use of the multiple data is not well linked and integrated among themselves. The purpose of this study is to examine the linkage and integration of multi-source data dispersed in various places in order to increase the utilization value, and to prepare a plan to solve the difficulties and to activate them. Main results of this study are as follows: Data integration and analysis were conducted by using real data. The Korea Health Panel Survey data and Life Time Use Survey data were integrated by using the nearest neighborhood hot deck method based on the exact distance function. The purpose of integrating the two data was to identify the possibility of creating integrated data on multi-source surveys, and to analyze the relationship between health behavior and life time use. Results of the integrated data analysis revealed a statistically significant difference in behavior of life time usage(essential time, duty time, free time, exercise time) by gender and age group. According to subjective health status, there were statistically significant differences in life time use: men and women in their 60s and older for essential time, duty time, free time, men in their 40s and 50s for duty time, free time and exercise time, and women in their 40s and 50s for duty time. The middle-aged usually have health problems such as onset of chronic diseases. This was appeared due to decreased time on work, housework, and other activities for treatment of diseases, or due to restricted activities caused by diseases. Such a group was perceiving to have poor subjective health status due to health problems. On the other hand, it was found that the group with poor subjective health status spent more exercise time for health care. As such, the results were similar to the previous studies on the relationship between subjective health status and life time use. Accordingly, data integration based on statistical matching methods can be regarded as having high data utilization. If more diverse data can be integrated in the future, various information could be used that was insufficient to be considered in the health field, so that various factors can be identified for countermeasures for the people’s health.