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Original article
- Storing information of stroke rehabilitation patients using blockchain technology: a software study
- Min Cheol Chang
- J Yeungnam Med Sci. 2022;39(2):98-107. Published online September 7, 2021
- DOI: https://doi.org/10.12701/yujm.2021.01368
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- 2 Web of Science
- 2 Crossref
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Abstract
PDF - Background
Stroke patients usually experience damage to multiple functions and a long rehabilitation period. Hence, there is a large volume of patient clinical information. It thus takes a long time for clinicians to identify the patient’s information and essential pieces of information may be overlooked. To solve this, we stored the essential clinical information of stroke patients in a blockchain and implemented the blockchain technology using the Java programming language.
Methods
We created a mini blockchain to store the medical information of patients using the Java programming language.
Results
After generating a unique pair of public/private keys for identity verification, a patient’s identity is verified by applying the Elliptic Curve Digital Signature Algorithm based on the generated keys. When the identity verification is complete, new medical data are stored in the transaction list and the generated transaction is verified. When verification is completed normally, the block hash value is derived using the transaction value and the hash value of the previous block. The hash value of the previous block is then stored in the generated block to interconnect the blocks.
Conclusion
We demonstrated that blockchain can be used to store and deliver the patient information of stroke patients. It may be difficult to directly implement the code that we developed in the medical field, but it can serve as a starting point for the creation of a blockchain system to be used in the field. -
Citations
Citations to this article as recorded by
- Prediction of motor outcome based on brain perfusion single photon emission computed tomography in corona radiata infarct
Eunjung Kong, Donghwi Park, Min Cheol Chang
International Journal of Neuroscience.2023; : 1. CrossRef - Use of QR Codes for Promoting a Home-Based Therapeutic Exercise in Patients with Lumbar Disc Herniation and Lumbar Spinal Stenosis: A Prospective Randomized Study
Min Cheol Chang, Donghwi Park, Yoo Jin Choo
Journal of Pain Research.2022; Volume 15: 4065. CrossRef
- Prediction of motor outcome based on brain perfusion single photon emission computed tomography in corona radiata infarct
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