This project aimed at identifying the characteristics of health data and thus determining its value. Each health-data characteristic provides different types of information, giving insight into the overall monetary value of the data. This is based on the premise that not all health data possesses the same monetary value, and hence some health data might have more monetary value attached to it. An example would be whether the data would contain any sensitive information, such as personally identifiable information, non-disclosure information, and confidential internal information [1].
In today’s data economy, individuals are reluctant to share their health data, one reason being that the value generated out of their health data is being paid to the institutions instead of the individual as the original data provider [2]. Moreover, the fear of a breach of data protection regulations would further explain why individuals may not want to share their health data, since the data could be compromised and accessed by unauthorised individuals. A third explanation for the said reluctance would be the lack of incentives in sharing health data.
Taking the above into account, this project adopted blockchain to increase the security of the data that would be processed. Additionally, the users were incentivised to share their information in return for tokens. These tokens could then be exchanged into a currency. The proposed solution for these issues was to provide a decentralised marketplace using blockchain technology to tokenise a person’s health data.
Figure 2 offers an overview of the proposed system. The user first inputs data from a webpage to be saved on the blockchain. This would prompt the option to share the user’s health data with different entities. Once the user and entity would reach an agreement on how the health information is to be shared, the user would receive tokens from the entity in return for sharing their health information.
Figure 1. Data characteristics of monetised health data
Figure 2. Overview of the system
Student: Dylan Kurt Catania
Supervisor: Prof. Lalit Garg