A Decentralized Blockchain-Node-Red-Cloud Architecture for Secure EHR Management and Novel Disease Prediction

In today’s healthcare landscape, where data is the backbone of effective care and seamless supply chains are essential, system inefficiencies and data vulnerabilities can seriously impact patient safety. This paper introduces a novel, integrated framework that combines Blockchain technology, Node-RED, and cloud computing to transform how healthcare data is managed and how emerging diseases are detected. A private Blockchain acts as the backbone for securely storing electronic health records (EHRs) and tracking supply chain activities, ensuring data integrity and traceability. To streamline real-time operations, Node-RED provides a user-friendly, visual programming interface that automates critical processes like prescription verification and inventory synchronization among healthcare stakeholders. Cloud infrastructure complements the Blockchain by handling high-volume data processing and analytics, helping the system scale without compromising performance. At the core of the framework lies the Enhanced Supervised Learning Chain Model (ESLCM), a machine learning model designed to analyse patient symptoms and regional health data. This model can identify unusual patterns that may signal the onset of novel diseases, making it a vital tool for early detection and pandemic preparedness. By combining transparency, automated workflows, and intelligent analytics with a strong commitment to data privacy, this integrated system empowers healthcare providers to respond faster, collaborate more effectively, and deliver smarter, more secure care in a world where every second matters.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2024-12-30
DOI
https://doi.org/10.52783/jisem.v9i4s.11203
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.00
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article

A Decentralized Blockchain-Node-Red-Cloud Architecture for Secure EHR Management and Novel Disease Prediction

Jayendra Jadhav
Journal of Information Systems Engineering & Management
Brain Tumor Detection and Classification
article

A Decentralized Blockchain-Node-Red-Cloud Architecture for Secure EHR Management and Novel Disease Prediction

Jayendra Jadhav
article en

Abstract

In today’s healthcare landscape, where data is the backbone of effective care and seamless supply chains are essential, system inefficiencies and data vulnerabilities can seriously impact patient safety. This paper introduces a novel, integrated framework that combines Blockchain technology, Node-RED, and cloud computing to transform how healthcare data is managed and how emerging diseases are detected. A private Blockchain acts as the backbone for securely storing electronic health records (EHRs) and tracking supply chain activities, ensuring data integrity and traceability. To streamline real-time operations, Node-RED provides a user-friendly, visual programming interface that automates critical processes like prescription verification and inventory synchronization among healthcare stakeholders. Cloud infrastructure complements the Blockchain by handling high-volume data processing and analytics, helping the system scale without compromising performance. At the core of the framework lies the Enhanced Supervised Learning Chain Model (ESLCM), a machine learning model designed to analyse patient symptoms and regional health data. This model can identify unusual patterns that may signal the onset of novel diseases, making it a vital tool for early detection and pandemic preparedness. By combining transparency, automated workflows, and intelligent analytics with a strong commitment to data privacy, this integrated system empowers healthcare providers to respond faster, collaborate more effectively, and deliver smarter, more secure care in a world where every second matters.

Journal of Information Systems Engineering & ManagementVol. 9(4s)
Openalex Percentile: Top 67%
Brain Tumor Detection and Classification
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