Evidence map›Paper›PMID 36271243›Full record

ArticleScientific reports2022

MRBSChain a novel scalable medical records binance smart chain framework enabling a paradigm shift in medical records management.

Suhasini Monga, Dilbag Singh

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Suhasini MongaDepartment of Computer Science and Engineering, Chaudhary Devi Lal University, Sirsa, HR, 125055, India. suhasini.monga@gmail.com.
Dilbag SinghDepartment of Computer Science and Engineering, Chaudhary Devi Lal University, Sirsa, HR, 125055, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical records management had always been a challenging in healthcare sector. Traditionally, medical records are handled either manually or electronically that are under the stewardship of hospitals/healthcare institutions. A patient centric approach is the new paradigm where patient is an inherent part of the healthcare ecosystem controlling the access and sharing of his/her personal medical care information. Medical care information requires robust security and privacy. Also there are other issues like confidentiality, interoperability, scalability, cost efficiency and timeliness that need to be addressed. To achieve these objectives, this paper proposes a novel-scalable patient centric yet privacy preserving framework for efficient and secure electronic medical records management. In addition, proposed system generates a unified trusted record and authentication role mapping for enforcing secure access control for medical records using complex encryption algorithms. This paper identifies 13 key performance factors for performance comparison of proposed framework with traditional models. Ethereum and Binance Smart Chain acted as a benchmark platform for performance evaluation of MRBSChain on the basis of three metrics (transaction cost, average block time and deployment cost).At last, a comparative analysis of MRBSChain with other state of art blockchain systems on the basis of execution time is presented in the paper.

Indexed as

BlockchainComputer SecurityEcosystemElectronic Health RecordsFemaleForms and Records ControlHumansMale

Identifiers

PMID36271243
PMCPMC9586928

What OpenQuestion holds

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LicenceCC BY
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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.