Secondly, data * * * lacks privacy protection. Data sharing will inevitably lead to the risk of data leakage in medical institutions, and data sharing is difficult to control. How to realize data sharing under the premise of fully ensuring data security is a difficult problem that must be solved as soon as possible.
Thirdly, the right of data sharing and circulation is difficult to determine, and data can be easily copied in the process of sharing and circulation. If the data can't be confirmed and the producers, users, managers and beneficiaries of the data can't be authorized accurately, which will seriously hinder the enjoyment and circulation of the data.
Finally, there is a lack of distribution mechanism for data sharing. The traditional data concentration method is difficult to quantify the actual data contribution of each unit, team and individual, so there is no good incentive mechanism. No matter how much data * * * enjoys and whether the data quality is good or bad, participants will get the same benefits. If there is no reasonable incentive mechanism, each participant will tend to enjoy his own data as little as possible, or not enjoy the data except the required data at all.
On the challenges faced by the development of medical big data, Qingteng Bian Xiao is here to share with you. If you are interested in big data engineering, I hope this article can help you. If you want to know more about the skills and information of data analysts and big data engineers, you can click on other articles on this site to learn.