PHR-NFT: Decentralized Blockchain Framework with Hyperledger and NFTs for Secure and Transparent Patient Health Records

Blockchain technology holds significant promise for healthcare by enhancing the security and integrity of patient health records (PHRs) through decentralized storage and transparent access. However, it has substantial limitations, including problems with scalability, high transaction costs, privacy concerns, and intricate stakeholder access management. This study presents PHR-NFT, a novel framework that strengthens PHR privacy by utilizing Hyperledger Fabric and non-fungible tokens (NFTs) to address these issues. PHR-NFT improves privacy and communication by letting patients keep control of their medical records while permitting temporary, permission-based access by medical professionals. PHR-NFT offers a transparent solution that increases trust among healthcare stakeholders through the robust and decentralized architecture of the Hyperledger Fabric. This study demonstrates the viability and effectiveness of the PHR-NFT framework through performance evaluations focused on transaction latency, throughput, and security. This research has valuable implications for enhancing data privacy and security in healthcare practices and insightful information about blockchain-based healthcare systems.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2024-11-20
DOI
https://doi.org/10.3390/app142210744
Citations
6
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
4.67

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PHR-NFT: Decentralized Blockchain Framework with Hyperledger and NFTs for Secure and Transparent Patient Health Records

Huwida Said, Nedaa Baker Al Barghuthi, Shini Girija, Faiza Hashim et al.
6 citations
Applied Sciences
Blockchain Technology Applications and Security
4.67
article

PHR-NFT: Decentralized Blockchain Framework with Hyperledger and NFTs for Secure and Transparent Patient Health Records

Huwida Said, Nedaa Baker Al Barghuthi, Shini Girija, Faiza Hashim, Sulafa Badi
article en
6 citations

Abstract

Blockchain technology holds significant promise for healthcare by enhancing the security and integrity of patient health records (PHRs) through decentralized storage and transparent access. However, it has substantial limitations, including problems with scalability, high transaction costs, privacy concerns, and intricate stakeholder access management. This study presents PHR-NFT, a novel framework that strengthens PHR privacy by utilizing Hyperledger Fabric and non-fungible tokens (NFTs) to address these issues. PHR-NFT improves privacy and communication by letting patients keep control of their medical records while permitting temporary, permission-based access by medical professionals. PHR-NFT offers a transparent solution that increases trust among healthcare stakeholders through the robust and decentralized architecture of the Hyperledger Fabric. This study demonstrates the viability and effectiveness of the PHR-NFT framework through performance evaluations focused on transaction latency, throughput, and security. This research has valuable implications for enhancing data privacy and security in healthcare practices and insightful information about blockchain-based healthcare systems.

Applied SciencesVol. 14(22)
Higher Colleges of Technology (AE), British University in Dubai (AE), United Arab Emirates University (AE), Zayed University (AE)
Zayed University
Openalex Percentile: Top 5%
Blockchain Technology Applications and Security
4.67
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.