Evidence map›Paper›PMID 35315778›Full record

ArticleJournal of medical Internet research2022

Privacy Preservation in Patient Information Exchange Systems Based on Blockchain: System Design Study.

Sejong Lee, Jaehyeon Kim, Yongseok Kwon, Teasung Kim, Sunghyun Cho

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

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  4. Enhancing Cancer Care through Blockchain Technology.Asian Pacific journal of cancer prevention : APJCP · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sejong LeeDepartment of Computer Science and Engineering, Hanyang University, Ansan, Republic of Korea.ORCID 0000-0001-9021-7008
Jaehyeon KimMajor in Bio-Artificial Intelligence, Hanyang University, Ansan, Republic of Korea.ORCID 0000-0001-9347-3680
Yongseok KwonDepartment of Computer Science and Engineering, Hanyang University, Ansan, Republic of Korea.ORCID 0000-0002-8202-2793
Teasung KimDepartment of Computer Science and Engineering, Hanyang University, Ansan, Republic of Korea.ORCID 0000-0001-9902-9097
Sunghyun ChoDepartment of Computer Science and Engineering, Hanyang University, Ansan, Republic of Korea.ORCID 0000-0002-1847-6088

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the increasing sophistication of the medical industry, various advanced medical services such as medical artificial intelligence, telemedicine, and personalized health care services have emerged. The demand for medical data is also rapidly increasing today because advanced medical services use medical data such as user data and electronic medical records (EMRs) to provide services. As a result, health care institutions and medical practitioners are researching various mechanisms and tools to feed medical data into their systems seamlessly. However, medical data contain sensitive personal information of patients. Therefore, ensuring security while meeting the demand for medical data is a very important problem in the information age for which a solution is required.

objectiveOur goal is to design a blockchain-based decentralized patient information exchange (PIE) system that can safely and efficiently share EMRs. The proposed system preserves patients' privacy in the EMRs through a medical information exchange process that includes data encryption and access control.

methodsWe propose a blockchain-based EMR-sharing system that allows patients to manage their EMRs scattered across multiple hospitals and share them with other users. Our PIE system protects the patient's EMR from security threats such as counterfeiting and privacy attacks during data sharing. In addition, it provides scalability by using distributed data-sharing methods to quickly share an EMR, regardless of its size or type. We implemented simulation models using Hyperledger Fabric, an open source blockchain framework.

resultsWe performed a simulation of the EMR-sharing process and compared it with previous works on blockchain-based medical systems to check the proposed system's performance. During the simulation, we found that it takes an average of 0.01014 (SD 0.0028) seconds to download 1 MB of EMR in our proposed PIE system. Moreover, it has been confirmed that data can be freely shared with other users regardless of the size or format of the data to be transmitted through the distributed data-sharing technique using the InterPlanetary File System. We conducted a security analysis to check whether the proposed security mechanism can effectively protect users of the EMR-sharing system from security threats such as data forgery or unauthorized access, and we found that the distributed ledger structure and re-encryption-based data encryption method can effectively protect users' EMRs from forgery and privacy leak threats and provide data integrity.

conclusionsBlockchain is a distributed ledger technology that provides data integrity to enable patient-centered health information exchange and access control. PIE systems integrate and manage fragmented patient EMRs through blockchain and protect users from security threats during the data exchange process among users. To increase safety and efficiency in the EMR-sharing process, we used access control using security levels, data encryption based on re-encryption, and a distributed data-sharing scheme.

Indexed as

BlockchainArtificial IntelligenceComputer SecurityConfidentialityHumansPrivacyconsortium blockchaindata securityelectronic medical recordsInterPlanetary File Systemmedical data managementpatient-centered medical systemprivacy preservationproxy re-encryptionsmart contract

Identifiers

PMID35315778
PMCPMC8984831

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.