Cited by 676Blockchain Technology Applications and SecurityElectronic Health Records SystemsBlockchain Technology in Education and Learning

The DOI matches its Crossref record; 45 of the 46 references it cites were found in a registry or an index; none of the 32 sources its claims cite is checked for support yet.

Blockchain in healthcare and health sciences—A scoping review

Open access
Hasselgren, Anton, Kralevska, Katina, Gligoroski, Danilo, Pedersen, Sindre A., Faxvaag, Arild·2020·International Journal of Medical Informatics

Abstract

BACKGROUND: Blockchain can be described as an immutable ledger, logging data entries in a decentralized manner. This new technology has been suggested to disrupt a wide range of data-driven domains, including the health domain. OBJECTIVE: The purpose of this study was to systematically review, assess and synthesize peer-reviewed publications utilizing/proposing to utilize blockchain to improve processes and services in healthcare, health sciences and health education. METHOD: A structured literature search on the topic was conducted in October 2018 relevant bibliographic databases. RESULT: 39 publications fulfilled the inclusion criteria. The result indicates that Electronic Health Records and Personal Health Records are the most targeted areas using blockchain technology. Access control, interoperability, provenance and data integrity are all issues that are meant to be improved by blockchain technology in this field. Ethereum and Hyperledger fabric seem to be the most used platforms/frameworks in this domain. CONCLUSION: This study shows that the endeavors of using blockchain technology in the health domain are increasing exponentially. There are areas within the health domain that potentially could be highly impacted by blockchain technology.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This scoping review systematically assessed 39 peer-reviewed publications on blockchain in healthcare, health sciences, and health education. It found that EHRs and PHRs are the most targeted areas, consortium blockchains and Ethereum/Hyperledger are common, but the field remains early and lacks evidence of real-world effects and regulatory compliance.

Key findings

  • Of 39 included publications, 43% targeted electronic health records, 15% personal health records, and 5% clinical trial support systems; 62% addressed some process of sharing health data.
  • Blockchain was proposed to improve access control in 35% of publications, interoperability in 27%, data integrity in 28%, and provenance in 12%.
  • Consortium blockchain was the preferred type (38%); Ethereum was used in 28%, Hyperledger Fabric in 10%, and Exonum in 4%; 36% developed a new blockchain and 21% did not specify a platform. PoW was the most frequent consensus algorithm (21%), PBFT was 15%, 41% did not state a consensus protocol, and 38% used smart contracts.
  • The average citation count was 21 ± 40 (up to March 2019); publications by year were 2016 (n = 4), 2017 (n = 11), and 2018 (n = 23); most studies were associated with Chinese (42%) or USA (20%) research institutes. Quality assessment total mean score was 5.7 ± 1.8, with a range of 1–9.

Methods

  • A structured literature search was conducted in October 2018 in MEDLINE, Embase, Cochrane Library, Scopus, Google Scholar, Compendex, Inspec, ACM, and IEEE, searching for “blockchain” combined with “health” and using backward/forward snowballing.
  • Titles, abstracts, and full articles were screened by reviewer 1, with doubtful cases reviewed by three additional reviewers; disagreements were resolved by discussion. Data were extracted into a pre-developed matrix and analyzed in Microsoft Excel.
  • Quality assessment used a tool adapted from Hölbl et al.; no papers were excluded in this process. All included papers were categorized as Proof-of-Concept design, and eleven were considered a hybrid between Proof-of-Concept and case-study design.

Limitations

  • The paper states that the review does not capture the whole picture, especially promising private-sector developments not covered in the included publications, such as genome management and medical credential systems.
  • The paper states that none of the included publications described how their blockchain-based solution complied with GDPR, HIPAA, or other national health data laws and regulations.
  • Evident from the text: many included publications failed to define their blockchain type, platform/framework, or consensus protocol, limiting comparability and feasibility assessment; the search was last updated in October 2018, so later work is not included.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.ijmedinf.2019.104040

Cites

45 of 45 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

47 Own result · 18 Not checked yet · 10 Own interpretation · 8 No basis given · 4 Own method

Verify all 32 references — free account

Show all 55 claims

  • Probably not a substantial claim. 25
  • It may state two separate claims as one. 17
32 of 32
  • The paper relies on this without support.

    Current literature provides little overview of applications that have been developed, tested and/or deployed.

    “current literature provides little overview of applications that have been developed, tested and/or deployed.”
  • The authors state this as an assumption.

    M-health will increase at a rapid pace in the coming years.

    “There is a reasonable assumption that m-health will increase at a rapid pace in the coming years and the need to verify and access m-health generated data by the health systems becomes crucial for the continued development of HIS and to insure that these data-driven systems stay up to date.”
  • The paper relies on this without support.

    Healthcare institutions are in critical demand for new and improved trust-preserving solutions.

    “Due to the over-arching importance of maintaining trust while satisfying an ever-increasing demand for exchange of data within the healthcare ecosystem, healthcare institutions are in critical demand for new and improved trust-preserving solutions.”
  • The paper relies on this without support.

    M-health is a rather new field and lacks a common data infrastructure and, to some degree, lacks common regulation around dealing with health data and getting the data accepted by the established health system.

    “M-health is a rather new field and lacks a common data infrastructure and, to some degree, lacks common regulation around dealing with health data and getting the data accepted by the established health system.”
  • The paper relies on this without support.

    There are promising developments in the private sector in other areas of the health sector that are not covered in the included publications for this review, for example genome management and medical credential systems.

    “There are promising developments in the private sector in other areas of the health sector that are not covered in the included publications for this review; for example, genome management and medical credential systems.”
  • The paper relies on this without support.

    The blockchain technology market in the global healthcare industrial sector is expected to cross $500 million by 2022.

    “This trend is also noticeable in the global healthcare industrial sector, where the blockchain technology market is expected to cross $500 million by 2022.”
6 of 6

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Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

4 of 4

Citations

Cites

Show all 46 references

Research works printed but not linked: 2

  1. blockchain.com [cited 2019 09.03]. Available from: https://www.blockchain.com/charts/n-transactions-total.
  2. Courtney, 1989, Some informal comments about integrity and the integrity workshop

Cited by

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Metadata

Authors
Hasselgren, A., Kralevska, K., Gligoroski, D., Pedersen, S. A., & Faxvaag, A.
Affiliations
Norwegian University of Science and Technology (NO)
Corresponding author
Hasselgren, Anton
Venue
International Journal of Medical Informatics
Publisher
Elsevier BV
Published
2020-02
Volume
134
Pages
104040
ISSN
1386-5056 (ISSN-L)
OpenAlex
W2996452324
Cited by
676
References
46
Citations by year
2026: 58 · 2025: 98 · 2024: 123 · 2023: 135 · 2022: 127 · 2021: 109 · 2020: 26
FWCI
11.40
Type
journal article
Language
en
Open access
Locations
  • International Journal of Medical Informatics (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by-nc-nd)
Topics
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
Keywords
blockchain, health care, electronic health records, personal health records, interoperability, data integrity, access control, provenance, Ethereum, Hyperledger Fabric, health education
MeSH terms
Blockchain, Delivery of Health Care, Humans, Health Records, Personal, Electronic Health Records, Quality Improvement, Health Information Exchange

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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