Blockchain technology and raft consensus for secure physician prescriptions and improved diagnoses in electronic healthcare systems.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
08 Jul 2024
Historique:
received: 25 12 2023
accepted: 03 07 2024
medline: 9 7 2024
pubmed: 9 7 2024
entrez: 8 7 2024
Statut: epublish

Résumé

With electronic healthcare systems undergoing rapid change, optimizing the crucial process of recording physician prescriptions is a task with major implications for patient care. The power of blockchain technology and the precision of the Raft consensus algorithm are combined in this article to create a revolutionary solution for this problem. In addition to addressing these issues, the proposed framework, by focusing on the challenges associated with physician prescriptions, is a breakthrough in a new era of security and dependability for the healthcare sector. The Raft algorithm is a cornerstone that improves the diagnostic decision-making process, increases confidence in patients, and sets a new standard for robust healthcare systems. In the proposed consensus algorithm, a weighted sum of two influencing factors including the physician acceptability and inter-physicians' reliability is used for selecting the participating physicians. An investigation is conducted to see how well the Raft algorithm performs in overcoming prescription-related roadblocks that support a compelling argument for improved patient care. Apart from its technological benefits, the proposed approach seeks to revolutionize the healthcare system by fostering trust between patients and providers. Raft's ability to communicate presents the proposed solution as an effective way to deal with healthcare issues and ensure security.

Identifiants

pubmed: 38977868
doi: 10.1038/s41598-024-66746-y
pii: 10.1038/s41598-024-66746-y
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

15692

Informations de copyright

© 2024. The Author(s).

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Auteurs

Behnaz Abdorrahimi (B)

Electrical Engineering Department, Imam Reza International University, Mashhad, Iran.

Atefeh Nekouie (A)

Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran.

Amir Masoud Rahmani (AM)

Future Technology Research Center, National Yunlin University of Science and Technology, Yunlin, Taiwan.

Jan Lansky (J)

Department of Computer Science and Mathematics, Faculty of Economic Studies, University of Finance and Administration, Prague, Czech Republic.

Vladimír Nulíček (V)

Department of Computer Science and Mathematics, Faculty of Economic Studies, University of Finance and Administration, Prague, Czech Republic.

Mehdi Hosseinzadeh (M)

Institute of Research and Development, Duy Tan University, Da Nang, Vietnam. mehdihosseinzadeh@duytan.edu.vn.
School of Medicine and Pharmacy, Duy Tan University, Da Nang, Vietnam. mehdihosseinzadeh@duytan.edu.vn.

Mohammad Hossein Moattar (MH)

Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran.

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