353 research outputs found

    A Unified Health Information System Framework for Connecting Data, People, Devices, and Systems

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    The COVID-19 pandemic has heightened the necessity for pervasive data and system interoperability to manage healthcare information and knowledge. There is an urgent need to better understand the role of interoperability in improving the societal responses to the pandemic. This paper explores data and system interoperability, a very specific area that could contribute to fighting COVID-19. Specifically, the authors propose a unified health information system framework to connect data, systems, and devices to increase interoperability and manage healthcare information and knowledge. A blockchain-based solution is also provided as a recommendation for improving the data and system interoperability in healthcare

    ICU data management - A permissioned blockchain approach

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    Since its origin in finance, blockchain have been revolutionizing data storage and sharing in many other sensitive areas. Being the focus of Permissioned Blockchains around privacy, confidentiality, immutability, interoperability and reliability, it fits perfectly within the data requisites of healthcare. Even more, with the surge of new iterations of more recent implementations based on smart-contracts/chaincode that has its focus on increasing efficiency and usability and ease of implementation. Intensive Medicine an area with such high data complexity and throughput, and high incidence of medical error and patient injury. As such, it's imperative the continuous research and implementation of new technologies that can make pertinent knowledge available through reliable and accurate data, thus providing appropriate problem-solving skills to physicians. This paper presents a solution, as part of the Intelligence Decision Support Systems for Intensive Medicine (ICDS4IM) project, which objective is to increase accuracy, confidentiality and value to data from vital sensors and monitors by assuring its immutability and controlled oversee.The work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Projects Scope: DSAIPA/DS/0084/2018

    A BLOCKCHAIN BASED POLICY FRAMEWORK FOR THE MANAGEMENT OF ELECTRONIC HEALTH RECORD (EHRS)

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    The rapid development of information technology during the last decade has greatly influenced all aspects of society, including individuals and enterprise organizations. Adopting new technologies by individuals and organizations depends on several factors, such as usability, available resources, support needed for adoption benefits, and return on investment, to mention a few. When it comes to the adoption of new technologies, one of the main challenges faced by organizations is the ability to effectively incorporate such technologies into their enterprise solutions to maximize the expected benefits. For the last several years, Blockchain technology has become a popular trend in a variety of sectors, attracting the attention of many governments and industries. Blockchain technology is a distributed ledger with the general purpose of information exchange that requires authentication and trust. It acts as an immutable ledger and allows for distributed, encrypted, and secure logging of digital transactions after the participating nodes or entities have reached a consensus. Because of the asymmetric cryptography and distributed consensus algorithms that have been built for users’ security and ledger consistency, this technology has gained a lot of attention. Blockchain has enormous potentials; however, as with any emerging technology, several drawbacks may exist and have negative consequences. To determine how the technology may be deployed, a framework is usually required. However, due to the lack of clear national and international standards for controlling and reducing risks associated with such technology, legal and organizational factors must be addressed before the technology can be implemented. The thesis herein is a proposal for such a new policy framework for Electronic Health Records (EHRs) management. Through the establishment of a new policy framework specifically related to Blockchain technology, this proposal aims to achieve the following: first, provide policies to govern sustainable management of the confidentiality, integrity, and availability of information concerning Blockchain applications and solution implementation across health care entities; and second, the prevention and reduction of related information security risks and threats

    Blockchain for Healthcare: Securing Patient Data and Enabling Trusted Artificial Intelligence

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    Advances in information technology are digitizing the healthcare domain with the aim of improved medical services, diagnostics, continuous monitoring using wearables, etc., at reduced costs. This digitization improves the ease of computation, storage and access of medical records which enables better treatment experiences for patients. However, it comes with a risk of cyber attacks and security and privacy concerns on this digital data. In this work, we propose a Blockchain based solution for healthcare records to address the security and privacy concerns which are currently not present in existing e-Health systems. This work also explores the potential of building trusted Artificial Intelligence models over Blockchain in e-Health, where a transparent platform for consent-based data sharing is designed. Provenance of the consent of individuals and traceability of data sources used for building and training the AI model is captured in an immutable distributed data store. The audit trail of the data access captured using Blockchain provides the data owner to understand the exposure of the data. It also helps the user to understand the revenue models that could be built on top of this framework for commercial data sharing to build trusted AI models

    A Review of Blockchain Technology Based Techniques to Preserve Privacy and to Secure for Electronic Health Records

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    Research has been done to broaden the block chain’s use cases outside of finance since Bitcoin introduced it. One sector where block chain is anticipated to have a big influence is healthcare. Researchers and practitioners in health informatics constantly struggle to keep up with the advancement of this field's new but quickly expanding body of research. This paper provides a thorough analysis of recent studies looking into the application of block chain based technology within the healthcare sector. Electronic health records (EHRs) are becoming a crucial tool for health care practitioners in achieving these objectives and providing high-quality treatment. Technology and regulatory barriers, such as concerns about results and privacy issues, make it difficult to use these technologies. Despite the fact that a variety of efforts have been introduced to focus on the specific privacy and security needs of future applications with functional parameters, there is still a need for research into the application, security and privacy complexities, and requirements of block chain based healthcare applications, as well as possible security threats and countermeasures. The primary objective of this article is to determine how to safeguard electronic health records (EHRs) using block chain technology in healthcare applications. It discusses contemporary HyperLedgerfabrics techniques, Interplanar file storage systems with block chain capabilities, privacy preservation techniques for EHRs, and recommender systems

    #Blockchain4EU: Blockchain for Industrial Transformations

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    The project #Blockchain4EU is a forward looking exploration of existing, emerging and potential applications based on Blockchain and other DLTs for industrial / non-financial sectors. It combined Science and Technology Studies with a transdisciplinary policy lab toolbox filled with frameworks from Foresight and Horizon Scanning, Behavioural Insights, or Participatory, Critical and Speculative Design. Amid unfolding and uncertain developments of the Blockchain space, our research signals a number of crucial opportunities and challenges around a technology that could record, secure and transfer any digitised transaction or process, and thus potentially affect large parts of current industrial landscapes. This report offers key insights for its implementation and uptake by industry, businesses and SMEs, together with science for policy strategic recommendations.JRC.I.2-Foresight, Behavioural Insights and Design for Polic

    A privacy preserving online learning framework for medical diagnosis applications

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    Electronic Health records are an important part of a digital healthcare system. Due to their significance, electronic health records have become a major target for hackers, and hospitals/clinics prefer to keep the records at local sites protected by adequate security measures. This introduces challenges in sharing health records. Sharing health records however, is critical in building an accurate online diagnosis framework. Most local sites have small data sets, and machine learning models developed locally based on small data sets, do not have knowledge about other data sets and learning models used at other sites. The work in this thesis utilizes the framework of coordinating the blockchain technology and online training mechanism in order to address the concerns of privacy and security in a methodical manner. Specifically, it integrates online learning with a permissioned blockchain network, using transaction metadata to broadcast a part of models while keeping patient health information private. This framework can treat different types of machine learning models using the same distributed dataset. The study also outlines the advantages and drawbacks of using blockchain technology to tackle the privacy-preserving predictive modeling problem and to improve interoperability amongst institutions. This study implements the proposed solutions for skin cancer diagnosis as a representative case and shows promising results in preserving security and providing high detection accuracy. The experimentation was done on ISIC dataset, and the results were 98.57, 99.13, 99.17 and 97,18 in terms of precision, accuracy, F1-score and recall, respectively
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