Decentralized Management of Medical Test Results Utilizing Blockchain, Smart Contracts, and NFTs

In today’s medical landscape, the effective management and availability of diagnostic data, including current and historical medical tests, play a critical role in inform-ing physicians’ therapeutic decisions. However, the conventional centralized storage system presents a significant impediment, particularly when patients switch healthcare providers. Given the sensitive nature of medical data, retrieving this information from a different healthcare facility can be fraught with challenges. While decentralized storage models using blockchain and smart contracts have been suggested as potential solutions, these methodologies often expose sensitive personal information due to the inherently open nature of data on the blockchain. Addressing these challenges, we present an innovative approach integrating Non-Fungible Tokens (NFTs) to facilitate the creation and sharing of medical document sets based on test results within a medical environment. This novel approach effectively balances data accessibility and security, introducing four key contributions: (a) We introduce a mechanism for sharing medical test results while preserving data privacy. (b) We offer a model for generating certified, NFT-based document sets that encapsulate these results.(c) We provide a proof-of-concept reflecting the proposed model’s functionality and (d) We deploy this proof-of-concept across four EVM-supported platforms—BNB Smart Chain, Fantom, Polygon, and Celo—to identify the most compatible platform for our proposed model. Our work underscores the potential of blockchain, smart contracts, and NFTs to revolutionize medical data management, demonstrating a practical solution to the challenges posed by centralized storage systems.

@article{L2023,
  title     = {Decentralized Management of Medical Test Results Utilizing Blockchain, Smart Contracts, and NFTs},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {14},
  number    = {8},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Quy T. L and Khanh H. V and Huong H. L and Khiem H. G and Phuc T. N and Ngan N. T. K and Triet M. N and Bang L. K and Trong D. P. N. and Hieu M. D. and Bao Q. T. and Khoa D. T.},
  doi       = {10.14569/IJACSA.2023.01408104},
  url       = {https://doi.org/10.14569/IJACSA.2023.01408104}
}