# Development of a MyData Platform Based on the Personal Health Record Data Sharing System in Korea
## 5 Discussion and Conclusions  
Health-related data play many roles in the field of medicine in terms of data economy, prediction, prevention and personalised health care [26]. This paper proposed HiMD, which is a medical data sharing platform that allows users to manage their own data by giving them the authority to set the boundaries by which their data are used. This research was supported by the MyData governmental policy project in accordance with the South Korean government's intentions to give users rightful ownership over their own medical data. The main functions include data consensus-setting functions for hospitals and companies, data searching, data downloading and data sharing. Through this platform, users have the ability to manage and view their data. This empowers the users when they engage the system. The system called 'HiMD' was designed to identify the usage status of individual health data through PHR scenarios in the MyData system. Three hospitals participated in platform testing. These hospitals agreed to provide health examination data, prescription data, DNA data and depression-related data. Additionally, four companies participated in platform testing by providing services for gene sequencing for cancer analysis, management of chronic disease, home meal replacement and mental healthcare. Then, user satisfaction and intention-to-use analyses were performed with a focus on various benefits provided through data ownership. All users were provided with informed consent. Then, a survey was conducted for users who used the system for more than 2 weeks. A total of 2533 real participants were recruited from the health examination centres of the participating medical institutions, although only 1269 agreed to participate in the survey. Socio-demographic results revealed that females comprised the majority of users with 991 participants (78.1%). According to related research, this may be the result of females being more sensitive to healthcare than males [27]. Demographic results also revealed the highest participation of 36.3% among adults aged 30 to 39 year (\(n=465\)), whereas the elderly over age 50 exhibited the lowest participation of 14.0% (\(n=178\)). This may be because relatively young adults are highly accepting of technology, whereas the elderly have a hard time adopting modern technology [28]. Additional research is required to determine how age influences the adoption of the proposed system. Data consensus results revealed a decrease in granted user permissions as the range and depth of permission increased. Specifically, almost all people allowed the simplest form of data allowance, which was only'searching' (\(n=1204\), 94.9%). 'Downloading', which is a more in-depth form of data allowance, exhibited the next rank of agreement (\(n=1161\), 91.5%). 'Sharing', which is an even more in-depth form of data allowance, naturally ranked third (\(n=1066\), 84.0%). Users who allowed commercial usage of their data by companies exhibited the lowest allowance ranking with only 79.4% (\(n=1007\)). This implies that although users are open to medical data sharing, they are sensitive to their data being used commercially. However, 79.4% is not a low percentage in absolute terms, which is a promising consideration. For users who agreed to open their medical data commercially (\(n=1007\), 79.4%), most were interested in DNA analysis (\(n=888\), 81.2%). These results could be used as baseline data reflecting user interest in the field of medical data when healthcare-related companies are conducting business. Satisfaction and intention-to-use analysis results revealed positive satisfaction and intention to use among participants. This proved that the majority of participants had a positive overall attitude towards the proposed system. The limitation of this research is that available personal health data that were utilized were limited. That is, the data provided from hospitals were restricted to health check-up data, drug prescription data and depression scale testing data.