Evidence map›Paper›PMID 40830150›Full record

ArticleScientific reports2025

Enhancing confidentiality and access control in electronic health record systems using a hybrid hashing blockchain framework.

D Gowtham Chakravarthy, R Gopi, Sivaram Murugan, Emerson Raja Joseph

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

4 authors.

D Gowtham ChakravarthyFaculty of Computer Science & Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, 641202, India.
R GopiFaculty of Computer Science & Engineering, Dhanalakshmi Srinivasan Engineering College, Perambalur, Tamil Nadu, 621212, India.
Sivaram MuruganDepartment of Computer Engineering, Faculty of Engineering and Natural Sciences, Sivas University of Science and Technology, Sivas, 58000, Turkey.
Emerson Raja JosephFaculty of Engineering and Technology, Multimedia University, Melaka, 75450, Malaysia. emerson.raja@mmu.edu.my.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Confidentiality and access control are essential to protect sensitive data, prevent cyber threats, ensure compliance, and avoid risks like identity theft. Hence, a framework towards secure patient Data access using Hybrid Integrated Hashing Method is introduced to ensure patient confidentiality and efficient data access in healthcare systems. Unlike conventional solutions that rely solely on standard blockchain and secure hash algorithm 256 for data protection, this proposed method integrates a multi-layer hybrid hashing approach combining dynamic hash chaining with temporal entropy encoding, making hash collisions virtually infeasible. A selective data compression mechanism is also embedded to maintain performance while preserving cryptographic strength. Additionally, the system employs role-based decentralized access control, enforced through smart contracts, enabling real-time permission verification and immutable audit trails. A simulated blockchain environment evaluates the proposed method's resilience against ransomware, hash collision, and data manipulation attacks. By employing a standard secure hash algorithm 256 hashing without compression or access-layer optimization, experimental findings show 27% reduced storage usage and 35% quicker data retrieval than typical blockchain-based electronic health record systems. The system shows robust resistance to illegal access compared to traditional role-based access control systems.

Indexed as

BlockchainConfidentialityControl systemHashingPatientSecurity

Identifiers

PMID40830150
PMCPMC12365062

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.