TY  - JOUR
AU  - Vashisth, Meenakshi 
AU  - Ranjan, Raju 
PY  - 2026
TI  - A Safe Method of Storing and Exchanging Electronic Health Records Using Smart Contracts and Blockchain Technology Using Fully Hashed Menezes-Qu-Vanstone Algorithm
JF  - Journal of Computer Science
VL  - 22
IS  - 2
DO  - 10.3844/jcssp.2026.517.530
UR  - https://thescipub.com/abstract/jcssp.2026.517.530
AB  - Electronic Health Records (EHRs) are essential for clinicians, patients, and researchers because they support timely care and informed decision-making. For this reason, digital health information must be collected, managed, and stored with strong protections to preserve privacy and prevent tampering. One approach to strengthening security is to use blockchain-based storage alongside smart contracts and controlled data sharing, which can help improve the integrity, access control, and traceability of health records. Hence, in this paper, we have described an archiving model for health records information. Records stored on blockchain are guaranteed not to have been tampered with or corrupted. By implementing chain of blocks technology, this paper describes an electronic medical data system because a distributed, decentralized digital ledger is used to store medical records. Patients retain complete control of the System construction plan for the new medical system, which includes FHMQV, the interplanetary file system. Medical records are stored on cloud servers. Transaction deployment and the costs have been computed. At this time, transaction expenses for physician enrolment are 0.00456 ETH, and for patient enrolment are 0.00478 ETH. Given the security advantages of blockchain-enabled health record exchange, the proposed model was evaluated in comparison with existing EHR sharing approaches. The results indicate measurable gains in operational efficiency and reduced costs, benefiting both healthcare organizations and patients. The model offers blockchain-based smart contracts that aim to maintain the permanence, transparency, and source of medical data. The method can efficiently eliminate the dependence of verification data consistency on people who are not parties to the authentication.