Evidence map›Paper›PMID 35002477›Full record

ArticleWorld wide web2022

CrowdMed-II: a blockchain-based framework for efficient consent management in health data sharing.

Chaochen Hu, Chao Li, Guigang Zhang, Zhiwei Lei, Mira Shah, Yong Zhang, Chunxiao Xing, Jinpeng Jiang, Renyi Bao

Abstract read
In one paragraph

Article in World wide web, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Pooled it
  2. Article
  3. Enhancing Cancer Care through Blockchain Technology.Asian Pacific journal of cancer prevention : APJCP · 2025
    Review
  4. 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

9 authors.

Chaochen HuDCST, BNRist, RIIT, Institute of Internet Industry, Tsinghua University, Beijing, China.
Chao LiBNRist, DCST, RIIT, Institute of Internet Industry, Tsinghua University, Beijing, China.
Guigang ZhangInstitute of Automation, Chinese Academy of Sciences, Beijing, China.
Zhiwei LeiJoint Research Center for Industry Trust Blockchain Application Technology, Tsinghua University, Beijing, China.
Mira ShahDCST, BNRist, RIIT, Institute of Internet Industry, Tsinghua University, Beijing, China.
Yong ZhangBNRist, DCST, RIIT, Institute of Internet Industry, Tsinghua University, Beijing, China.
Chunxiao XingBNRist, DCST, RIIT, Institute of Internet Industry, Tsinghua University, Beijing, China.
Jinpeng JiangYidu Cloud (Beijing) Technology Co., Ltd., Beijing, China.
Renyi BaoYidu Cloud (Beijing) Technology Co., Ltd., Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The healthcare industry faces serious problems with health data. Firstly, health data is fragmented and its quality needs to be improved. Data fragmentation means that it is difficult to integrate the patient data stored by multiple health service providers. The quality of these heterogeneous data also needs to be improved for better utilization. Secondly, data sharing among patients, healthcare service providers and medical researchers is inadequate. Thirdly, while sharing health data, patients' right to privacy must be protected, and patients should have authority over who can access their data. In traditional health data sharing system, because of centralized management, data can easily be stolen, manipulated. These systems also ignore patient's authority and privacy. Researchers have proposed some blockchain-based health data sharing solutions where blockchain is used for consensus management. Blockchain enables multiple parties who do not fully trust each other to exchange their data. However, the practice of smart contracts supporting these solutions has not been studied in detail. We propose CrowdMed-II, a health data management framework based on blockchain, which could address the above-mentioned problems of health data. We study the design of major smart contracts in our framework and propose two smart contract structures. We also introduce a novel search contract for searching patients in the framework. We evaluate their efficiency based on the execution costs on Ethereum. Our design improves on those previously proposed, lowering the computational costs of the framework. This allows the framework to operate at scale and is more feasible for widespread adoption.

Indexed as

BlockchainConsent managementHealth dataSmart contracts

Identifiers

PMID35002477
PMCPMC8720166

What OpenQuestion holds

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LicenceCC BY
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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.