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Blockchain Technology: Applications in Health Care
Abstract
B lockchain technology has gained substantial attention in recent years with increased interest in several diverse fields, including the healthcare industry.Blockchain offers a secure, distributed database that can operate without a central authority or administrator.Blockchain uses a distributed, peer-to-peer network to make a continuous, growing list of ordered records called blocks to form a digital ledger.Each transaction, represented in a cryptographically signed block, is then automatically validated by the network itself.Blockchain has also garnered interest as a platform to improve the authenticity and transparency of healthcare data through many use cases, from maintaining permissions in electronic health records (EHR) to streamlining claims processing.In this article, we describe the basics of blockchain and illustrate current and future applications of this technology within the healthcare industry. Healthcare Applications of BlockchainThis interest and momentum has now extended to healthcare information technology.Realizing the potential relevance and importance of blockchain in health care, the Office of the National Coordinator for Health Information Technology,
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“Yet, prior research has made limited attempts to holistically encapsulate extant knowledge by utilizing systematic literature reviews (SLRs) (e.g.Angraal et al., 2017;Hölbl et al., 2018;Agbo et al., 2019;O'Donoghue et al., 2019;Jaoude & Saade, 2019).”
From Blockchain in healthcare: A systematic literature review, synthesizing framework and future research agenda (2020) · cites this paper as Angraal et al., 2017
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“Gained a substantial attention in recent years T, the blockchain technology gained substantial popularity in recent years primarily due to the popularity of the Bitcoin crypto currency, was previously has been proposed as a medium for health care data storage solutions [94, 95] and as a tool for to improving thee transparency in clinical trials [96].”
From Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare (2018) · cites this paper as [95]
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Metadata
- Authors
- Angraal, S., Krumholz, H. M., & Schulz, W. L.
- Affiliations
- Yale New Haven Hospital (US)
- Venue
- Circulation Cardiovascular Quality and Outcomes
- Published
- 2017-09
- Volume
- 10
- Issue
- 9
- ISSN
- 1941-7705 (ISSN-L)
- 1941-7713
- OpenAlex
- W2754931682
- Cited by
- 430
- References
- 4
- Citations by year
- 2026: 19 · 2025: 43 · 2024: 44 · 2023: 63 · 2022: 49 · 2021: 57 · 2020: 71 · 2019: 53 · 2018: 28 · 2017: 3
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Circulation Cardiovascular Quality and Outcomes (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- blockchain, health information technology, electronic health records, data security, data transparency, peer-to-peer networks, distributed ledger technology, claims management
- MeSH terms
- Administrative Claims, Healthcare, Confidentiality, Database Management Systems, Diffusion of Innovation, Humans, Insurance Claim Review, Computer Security, Biomedical Technology, Electronic Health Records
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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