Personal Health Information De-identified Performing Methods in Big Data Environments

Abstract

The field that shows the most promise among the application areas of Big Data is the medical sector. We must first deal with the problems of the invasion of privacy and misuse of personal information before we can utilize personal health information. There is a method known as the de-identification of personal health information which is one of the methods that can be used to perform the tasks of the protection and the utilization of personal health information at the same time. De-identification refers to the process of making it impossible to know the identity of an individual just by the information that is revealed. The biggest problem related to de-identification is the phenomenon of re-identification. Even with information that at first cannot be used to readily identify an individual, when enough of it has accumulated in various categories, it may become possible to identify the hidden individual behind it. What makes de-identification difficult is that one cannot completely rule out the possibility of re-identification, and that the information becomes an object of much regulatory legislation if it is re-identified as personal information. Thus, it is a priority to reach an agreement among the many parties involved since we need to organize the data into categories that are actually used. This study seeks to analyze the current state of de-identification measures which are some of the protective measures for personal information for the safe utilization of Big Data in the medical sector, both in and out of Korea, and to propose implementation plans for safe de-identification. Furthermore, this study advocates an active consideration of the establishment of a central tower agency which will be able to carry out the much-needed continuous monitoring for re-identification as well as the assessment of the adequacy of the de-identification methods.