Abstract
Electronic Medical Records (EMRs) are crucial to modern healthcare. However, traditional relational databases fail to fulfill increased expectations for integrity, auditability, and compliance in regulated environments. This paper proposes a Hybrid Blockchain Migration Framework that integrates a conventional MySQL-based EMR system (OpenMRS) with a permissioned blockchain network (Hyperledger Fabric). Sensitive data fields are selectively mirrored to the blockchain, ensuring tamper-evident logging while retaining the high performance of SQL for routine operations. A middleware layer, implemented using Java Spring Boot, monitors changes in the EMR and commits cryptographic hashes and metadata to the blockchain in near real-time. We evaluate the hybrid system against both standalone MySQL and full-blockchain implementations using controlled benchmarks, analyzing latency, throughput, resource utilization, and auditability. Results show that the hybrid architecture sustains near-native responsiveness (median 2.1 ms versus 1.6 ms for pure MySQL and 60.5 ms for Fabric) and delivers 480 Transaction Per Second (TPS), while incurring only modest overhead (47% of i7-9750H CPU, 1.15 GB RAM) and enhancing data integrity and compliance with regulations such as Oman’s Personal Data Protection Law (PDPL). The framework is extensible to multi-institutional deployments and supports regulatory alignment, making it a viable pathway for blockchain adoption in clinical settings.
Data availability
The datasets generated and analysed during the current study were produced using a synthetic data generation script that creates artificial patient records based on common Omani first and family names. No real patient information or personally identifiable data were used. The synthetic dataset used for system benchmarking and blockchain migration testing is therefore fully de-identified and does not contain any real Electronic Medical Record (EMR) data. The data generation code, along with the sample synthetic dataset, is available in the [GitHub repository — link to be added upon acceptance]. Researchers can reproduce or extend the dataset by running the provided script, which uses randomized values for demographic and physiological parameters (e.g., height, weight, blood pressure) generated within medically plausible ranges. All synthetic data used in this study are compliant with the Oman Personal Data Protection Law (PDPL) since no identifiable or sensitive personal data were processed. Additional files or further materials are available from the corresponding author upon reasonable request.
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During the preparation of this work, the author(s) used ChatGPT by OpenAI to improve language clarity and readability. After using this tool, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.
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Ahmed Al-Busaidi conducted the research, designed and implemented the hybrid blockchain framework, performed the experiments, analyzed the results, and prepared the manuscript. Mani Joseph, Mohamed Sirajudee, and P. Vijaya. supervised the research, provided technical guidance, contributed to the interpretation of results, and reviewed and refined the manuscript. All authors approved the final version of the manuscript.
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Al-Busaidi, A., Mani, J., Yoosuf, M.S. et al. A hybrid blockchain migration framework for converting traditional databases into blockchain-based EMR systems. Sci Rep (2026). https://doi.org/10.1038/s41598-026-36787-6
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DOI: https://doi.org/10.1038/s41598-026-36787-6
