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Blockchain-Enabled Electronic Health Record Model for Managing Patients' Vital Data and Medical Reports
Aditi Sharma1, Rajesh Kumar Kaushal1, Naveen Kumar Chitkara1
1Research Scholar, Department of Computer Science and Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.
Blockchain in Healthcare Today
|May 28, 2026
Summary
The Internet of Medical Things (IoMT) enables remote patient monitoring but raises data security concerns. This study introduces a Hyperledger Fabric model for secure IoMT data management, ensuring reliable storage and retrieval of medical images.
Area of Science:
- Computer Science
- Health Informatics
- Cybersecurity
Background:
- The Internet of Medical Things (IoMT) facilitates remote patient care using sensors but generates large datasets, posing security and privacy risks.
- High-dimensional medical data are crucial for diagnostics and treatment but are often disconnected from secure electronic health record systems.
- Existing systems struggle to securely manage and integrate the vast amounts of data generated by remote patient monitoring.
Purpose of the Study:
- To develop and evaluate a secure remote patient monitoring model using Hyperledger Fabric for managing medical imaging data.
- To address the limitations of current systems in securely storing and retrieving high-dimensional medical data from IoMT devices.
- To enhance the integration of blockchain technology with remote patient monitoring for improved data security and accessibility.
Main Methods:
- A Hyperledger Fabric-based model was designed for secure remote patient monitoring, storing vital signs on-chain and medical images off-chain in the InterPlanetary File System.
- The system utilizes two organizations, a single channel, and Raft consensus for data consistency and high performance.
- Performance was evaluated through transaction throughput and latency tests under varying data transfer rates.
Main Results:
- The proposed system demonstrated high throughput, near the send rate up to 90 TPS, peaking at 117.04 TPS at 150 TPS send rate.
- No transactions were lost during testing, indicating high system reliability and successful transaction processing.
- Latency for operations ranged from 0.21 to 2.24 seconds, with read operations consistently at 0.01 seconds.
Conclusions:
- The Hyperledger Fabric-based model provides a secure and reliable solution for remote patient monitoring and medical image management.
- The system effectively addresses security and privacy concerns associated with IoMT data, ensuring data integrity and accessibility.
- The demonstrated performance metrics suggest the model's suitability for real-world implementation in healthcare settings.
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