Evidence map›Paper›PMID 33007951›Full record

ArticleInternational journal of environmental research and public health2020

Blockchain in Healthcare: Insights on COVID-19.

Antonio Fusco, Grazia Dicuonzo, Vittorio Dell'Atti, Marco Tatullo

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
–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

33 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
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  5. Article
  6. Clinical Impact of "Real World Data" and Blockchain on Public Health: A Scoping Review.International journal of environmental research and public health · 2024
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  9. Review
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  11. Article
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  14. Tamper-proof multitenant data storage using blockchain.Peer-to-peer networking and applications · 2023
    Article
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  16. Article
  17. Observational
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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

4 authors.

Antonio FuscoDepartment of Economics, Management and Business Law, University of Bari Aldo Moro, 70124 Bari, Italy.
Grazia DicuonzoDepartment of Economics, Management and Business Law, University of Bari Aldo Moro, 70124 Bari, Italy.
Vittorio Dell'AttiDepartment of Economics, Management and Business Law, University of Bari Aldo Moro, 70124 Bari, Italy.
Marco TatulloDepartment of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari ALDO MORO, 70124 Bari, Italy.ORCID 0000-0001-7340-0708

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SARS-CoV2 pandemic has impacted risk management globally. Blockchain has been increasingly applied to healthcare management, as a strategic tool to strengthen operative protocols and to create the proper basis for an efficient and effective evidence-based decisional process. We aim to validate blockchain in healthcare, and to suggest a trace-route for a COVID19-safe clinical practice. The use of blockchain in combination with artificial intelligence systems allows the creation of a generalizable predictive system that could contribute to the containment of pandemic risk on national territory. A SWOT analysis of the adoption of a blockchain-based prediction model in healthcare and SARS-CoV-2 infection has been carried out to underline opportunities and limits to its adoption. Blockchain could play a strategic role in future digital healthcare: specifically, it may work to improve COVID19-safe clinical practice. The main concepts, and particularly those related to clinical workflow, obtainable from different blockchain-based models have been reported here and critically discussed.

Indexed as

Artificial IntelligenceBlockchainCoronavirus InfectionsPandemicsPneumonia, ViralBetacoronavirusCOVID-19Delivery of Health CareHumansSARS-CoV-2Workflowartificial intelligenceblockchainCOVID-19global healthhealthcare management

Identifiers

PMID33007951
PMCPMC7579329

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.