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<p>The rapid growth of the Internet of Medical Things (IoMT) necessitates secure and efficient systems for managing sensitive healthcare data. Blockchain technology provides a robust solution by ensuring data integrity, immutability, and security, which fosters trust among stakeholders and facilitates seamless data sharing. Complementing this, Apache Kafka enables efficient real-time data streaming from various IoMT devices, allowing healthcare providers to access critical information quickly. In this research, we propose a secure Electronic Health Record (EHR) system called KB-IoMT, integrating Kafka with blockchain technology. We present algorithms for key processes, including secure node registration, proof of work, block creation, and data transmission, which ensure that medical data is securely mined, validated, and distributed. Experimental results demonstrate that the system achieves an average transaction throughput of 19.2 TPS and maintains transmission latency below 9&#xa0;s for high-volume workloads, validating its suitability for real-time EHR management in dynamic healthcare environments.</p>

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Blockchain-Enhanced Electronic Health Records: A Kafka-Based Approach for IoMT Integration

  • 期刊论文

  • 发表日期：

    2026年2月18日

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  • Nikita Tiwari,
  • Pradeep Kumar Biswal,
  • Prakash Ranjan

摘要

The rapid growth of the Internet of Medical Things (IoMT) necessitates secure and efficient systems for managing sensitive healthcare data. Blockchain technology provides a robust solution by ensuring data integrity, immutability, and security, which fosters trust among stakeholders and facilitates seamless data sharing. Complementing this, Apache Kafka enables efficient real-time data streaming from various IoMT devices, allowing healthcare providers to access critical information quickly. In this research, we propose a secure Electronic Health Record (EHR) system called KB-IoMT, integrating Kafka with blockchain technology. We present algorithms for key processes, including secure node registration, proof of work, block creation, and data transmission, which ensure that medical data is securely mined, validated, and distributed. Experimental results demonstrate that the system achieves an average transaction throughput of 19.2 TPS and maintains transmission latency below 9 s for high-volume workloads, validating its suitability for real-time EHR management in dynamic healthcare environments.