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

AbstractThe 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.

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CanDIG: Secure Federated Genomic Queries and Analyses Across Jurisdictions

10.1101/2021.03.30.434101 ◽

2021 ◽

Author(s):

Lewis Jonathan Dursi ◽

Zoltan Bozoky ◽

Richard de Borja ◽

Jimmy Li ◽

David Bujold ◽

...

Keyword(s):

Data Sharing ◽

Critical Mass ◽

Heterogeneous Data ◽

Health Data ◽

Large Datasets ◽

Security Requirements ◽

Precision Oncology ◽

Omics Data ◽

Data Types ◽

Privacy And Security

Rapid expansions of bioinformatics and computational biology have broadened the collection and use of -omics data including genomic, transcriptomic, methylomic and a myriad of other health data types, in the clinic and the laboratory. Both clinical and research uses of such data require co-analysis with large datasets, for which participant privacy and the need for data custodian controls must remain paramount. This is particularly challenging in multi-jurisdictional settings, such as Canada, where health privacy and security requirements are often heterogeneous. Data federation presents a solution to this, allowing for integration and analysis of large datasets from various sites while abiding by local policies. The Canadian Distributed Infrastructure for Genomics platform (CanDIG) enables federated querying and analysis of -omics and health data while keeping that data local and under local control. It builds upon existing infrastructures to connect five health and research institutions across Canada, relies heavily on standards and tooling brought together by the Global Alliance for Genomics and Health (GA4GH), implements a clear division of responsibilities among its participants and adheres to international data sharing standards. Participating researchers and clinicians can therefore contribute to and quickly access a critical mass of -omics data across a national network in a manner that takes into account the multi-jurisdictional nature of our privacy and security policies. Through this, CanDIG gives medical and research communities the tools needed to use and analyze the ever-growing amount of -omics data available to them in order to improve our understanding and treatment of various conditions and diseases. CanDIG is being used to make genomic and phenotypic data available for querying across Canada as part of data sharing for five leading pan-Canadian projects including the Terry Fox Comprehensive Cancer Care Centre Consortium Network (TF4CN) and Terry Fox PRecision Oncology For Young peopLE (PROFYLE), and making data from provincial projects such as POG (Personalized Onco-Genomics) more widely available.

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Secure and Privacy-Preserving Data Sharing and Collaboration in Mobile Healthcare Social Networks of Smart Cities

Security and Communication Networks ◽

10.1155/2017/6426495 ◽

2017 ◽

Vol 2017 ◽

pp. 1-12 ◽

Cited By ~ 9

Author(s):

Qinlong Huang ◽

Licheng Wang ◽

Yixian Yang

Keyword(s):

Social Networks ◽

Data Sharing ◽

Service Providers ◽

Smart Cities ◽

Data Encryption ◽

Health Data ◽

Security And Privacy ◽

Broadcast Encryption ◽

Social Data ◽

Mobile Healthcare

Mobile healthcare social networks (MHSN) integrated with connected medical sensors and cloud-based health data storage provide preventive and curative health services in smart cities. The fusion of social data together with real-time health data facilitates a novel paradigm of healthcare big data analysis. However, the collaboration of healthcare and social network service providers may pose a series of security and privacy issues. In this paper, we propose a secure health and social data sharing and collaboration scheme in MHSN. To preserve the data privacy, we realize secure and fine-grained health data and social data sharing with attribute-based encryption and identity-based broadcast encryption techniques, respectively, which allows patients to share their private personal data securely. In order to achieve enhanced data collaboration, we allow the healthcare analyzers to access both the reencrypted health data and the social data with authorization from the data owner based on proxy reencryption. Specifically, most of the health data encryption and decryption computations are outsourced from resource-constrained mobile devices to a health cloud, and the decryption of the healthcare analyzer incurs a low cost. The security and performance analysis results show the security and efficiency of our scheme.

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Smarter Smart Contracts: Efficient Consent Management in Health Data Sharing

Web and Big Data - Lecture Notes in Computer Science ◽

10.1007/978-3-030-60290-1_11 ◽

2020 ◽

pp. 141-155

Author(s):

Mira Shah ◽

Chao Li ◽

Ming Sheng ◽

Yong Zhang ◽

Chunxiao Xing

Keyword(s):

Data Sharing ◽

Health Data ◽

Smart Contracts

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Proactive Legal Design for Health Data Sharing Based on Smart Contracts

Smart Contracts ◽

10.5040/9781509937059.ch-005 ◽

2021 ◽

Author(s):

Arianna Rossi ◽

Helena Haapio

Keyword(s):

Data Sharing ◽

Health Data ◽

Smart Contracts

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Innovative Mobile E-Healthcare Systems: A New Rule-Based Cache Replacement Strategy Using Least Profit Values

Mobile Information Systems ◽

10.1155/2016/6141828 ◽

2016 ◽

Vol 2016 ◽

pp. 1-9 ◽

Cited By ~ 3

Author(s):

Ramzi A. Haraty

Keyword(s):

Health Service ◽

Service Providers ◽

Content Distribution ◽

Distribution Network ◽

Data Retrieval ◽

Health Data ◽

Cache Replacement ◽

Content Distribution Network ◽

Rule Based ◽

Health Service Providers

Providing and managing e-health data from heterogeneous and ubiquitous e-health service providers in a content distribution network (CDN) for providing e-health services is a challenging task. A content distribution network is normally utilized to cache e-health media contents such as real-time medical images and videos. Efficient management, storage, and caching of distributed e-health data in a CDN or in a cloud computing environment of mobile patients facilitate that doctors, health care professionals, and other e-health service providers have immediate access to e-health information for efficient decision making as well as better treatment. Caching is one of the key methods in distributed computing environments to improve the performance of data retrieval. To find which item in the cache can be evicted and replaced, cache replacement algorithms are used. Many caching approaches are proposed, but the SACCS—Scalable Asynchronous Cache Consistency Scheme—has proved to be more scalable than the others. In this work, we propose a new cache replacement algorithm—Profit SACCS—that is based on the rule-based least profit value. It replaces the least recently used strategy that SACCS uses. A comparison with different cache replacement strategies is also presented.

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The Need for Machine-Processable Agreements in Health Data Management

Algorithms ◽

10.3390/a13040087 ◽

2020 ◽

Vol 13 (4) ◽

pp. 87

Author(s):

George Konstantinidis ◽

Adriane Chapman ◽

Mark J. Weal ◽

Ahmed Alzubaidi ◽

Lisa M. Ballard ◽

...

Keyword(s):

Data Processing ◽

Data Management ◽

Data Sharing ◽

Medical Information ◽

Service Providers ◽

Personal Data ◽

Health Data ◽

Coarse Grained ◽

Semantic Web Technologies ◽

Fine Grained

Data processing agreements in health data management are laid out by organisations in monolithic “Terms and Conditions” documents written in natural legal language. These top-down policies usually protect the interest of the service providers, rather than the data owners. They are coarse-grained and do not allow for more than a few opt-in or opt-out options for individuals to express their consent on personal data processing, and these options often do not transfer to software as they were intended to. In this paper, we study the problem of health data sharing and we advocate the need for individuals to describe their personal contract of data usage in a formal, machine-processable language. We develop an application for sharing patient genomic information and test results, and use interactions with patients and clinicians in order to identify the particular peculiarities a privacy/policy/consent language should offer in this complicated domain. We present how Semantic Web technologies can have a central role in this approach by providing the formal tools and features required in such a language. We present our ongoing approach to construct an ontology-based framework and a policy language that allows patients and clinicians to express fine-grained consent, preferences or suggestions on sharing medical information. Our language offers unique features such as multi-party ownership of data or data sharing dependencies. We evaluate the landscape of policy languages from different areas, and show how they are lacking major requirements needed in health data management. In addition to enabling patients, our approach helps organisations increase technological capabilities, abide by legal requirements, and save resources.

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Perspective of Cikahuripan Villagers on Traditional Health Service Provisions in Government Regulation No. 103 Year 2014

Althea Medical Journal ◽

10.15850/amj.v7n3.1912 ◽

2020 ◽

pp. 159-164

Author(s):

Hashfi Khairuddin ◽

M. Rizal Chaidir ◽

Deni K. Sunjaya

Keyword(s):

Rural Communities ◽

Health Service ◽

Health Services ◽

Government Regulation ◽

Service Providers ◽

Traditional Health ◽

Health Service Providers ◽

Negative Case ◽

The Government ◽

Service Provisions

Background: Traditional health service is one of the health services that is still currently used in Indonesia, especially in rural communities. The government has been regulating these services since 2014. Despite its long existence, there is a recent increase of potential regulation violation among traditional health service providers. This study aimed to explore the perspective of the Cikahuripan Villagers on Government Regulation on traditional health services. Methods: This was a qualitative study using in-depth interviews and direct observations on traditional health services in Cikahuripan Village. Sixteen informants consisting of 8 villagers who met the inclusion criteria and another 8 informants in the triangulation negative case analysis, member checking, peer debriefing, and observation was involved. Results: There were two different perspectives in the community on traditional health service provisions in the Government Regulation. Supporters of the regulation believed that the regulation would make traditional health services more responsive and safer, which would improve service quality and health benefits as well as imposing effective sanctions. In contrast, the opposition believed that regulations were too late, would make the costs for licensing expensive, and too complicated. Conclusion: There are two different public perspectives on the regulation of traditional health services, which are supporting and opposing the regulation. It is expected that the local government create a derivative of the regulation by making adjustment to the community’s situation.

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