An Efficient Secure Sharing of Electronic Health Records Using IoT-Based Hyperledger Blockchain

Table 1

A comparison of blockchain technology’s medical record management for the healthcare industry.

References	Blockchain technology	Merits	Demerits	Type of medical data
Castaldo and Cinque [31]	Private blockchain (proof-of ownership)	Secure sharing of information for healthcare and enhanced auditing procedures	The cross-border interchange of e-health data are restricted to Europe	EHR
Yue et al. [32]	Private blockchain	Blockchain-based artificial intelligence system for healthcare data sharing privacy control	The suggested method was not scalable, and there was no guarantee that the data would be available (sharing of E-health data is limited)	EHR and PHR
Patel [33]	Proof-of-Stake	Decentralized and secure medical imaging data sharing	Interoperability and privacy concerns are not taken into account by the suggested solution	Medical image records
Hussain et al. [34]	Hash enabled blockchain platform	Sharing of medical records for administrative, clinical, and scientific reasons	Confidentiality and access control are ignored	EHR
Genestier et al. [35]	Hyperledger platform	Consent management is used in electronic health systems to manage and share personal data	There is no access control and no thorough permission procedure at all	EMR
Omar et al. [36]	Consortium blockchain	Sharing medical records with strong security via paired encryption and signatures	The suggested remedy lacks complete automation and functionality	Medical records
Babu et al. [37]	Health records’ security	Improved healthcare applications’ scalability, flexibility, security, and accessibility	Blockchain-based security solutions have greater costs and need to comply with regulations	Hyperledger fabric
Tiwari et al. [38]	Secure issue of IoT-based health monitoring system	Transactional data availability, security, integrity, and storage concerns	Performance measurements are not used to evaluate the suggested method	Hyperledger fabric
Pelekoudas-Oikonomou et al. [39]	Examines the edge learning and IMoT devices	Numerous aspects, including face mask recognition, fever detection, and patient cough sound analysis at home, were examined	The suggested solution’s accuracy in using actual subjects is not tested	Hyperledger Fabric and Ethereum