Evidence map›Paper›PMID 39789305›Full record

SynthesisMedical & biological engineering & computing2025

A systematic review of the blockchain application in healthcare research domain: toward a unified conceptual model.

Seyma Cihan, Nebi Yılmaz, Adnan Ozsoy, Oya Deniz Beyan

Abstract readSystematic Review
In one paragraph

Synthesis in Medical & biological engineering & computing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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.

Seyma CihanScientific and Technological Research Council of Turkey (Tubitak), Ankara, Turkey. seyma.cihan@tubitak.gov.tr.ORCID http://orcid.org/0000-0001-6267-2441
Nebi YılmazComputer Engineering Department, Hacettepe University, Ankara, Turkey.
Adnan OzsoyComputer Engineering Department, Hacettepe University, Ankara, Turkey.
Oya Deniz BeyanFaculty of Medicine and University Hospital Cologne, Institute for Medical Cologne, Cologne, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, research on blockchain applications in the healthcare research domain has attracted increasing attention due to its strong potential. However, the existing literature reveals limited studies on defining use cases of blockchain in clinical research, categorizing and comparing available studies. Therefore, this study aims to explore the significant potential and use cases of blockchain in clinical research through a comprehensive systematic literature review (SLR). To thoroughly investigate all aspects of the subject, we analyzed primary studies based on research questions (RQs) and developed a unified conceptual model using step-based model creation. Studies from 2015 to 2023 were reviewed, and 34 primary studies were comprehensively analyzed by using the PICO template. In our findings, privacy emerged as the most frequently cited requirement in clinical research. The most mentioned use cases for blockchain are ensuring data immutability and security. A significant issue identified beyond the common blockchain limitations of capacity and scalability is the lack of standards for compliance with legal frameworks like GDPR and HIPAA. After all these efforts, we developed a conceptual model, which, to our best knowledge, is the first in the literature to support software developers and clinical researchers in developing and using blockchain-based research platforms efficiently.

Indexed as

Biomedical ResearchBlockchainModels, TheoreticalComputer SecurityHumansBlockchain technologyClinical trialsConceptual modelHealthcare researchSystematic literature review

Identifiers

PMID39789305
PMCPMC12064621

What OpenQuestion holds

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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.