Performance Evaluation of a Patient-Centric Blockchain-based Healthcare Records Management Framework
08 Jul 2020-
TL;DR: The proposed BlockHR system enables healthcare providers to enter the patients' medical record data to the blockchain network and allows patients to enter their social data such as sleeping habits, physical activities, and current location and provides support to doctors for better diagnosis and prognosis.
Abstract: Healthcare records management system has been revolutionized over the last decade aiming to provide accurate, efficient and enhanced patient care. The existing management system is either based on a client/server approach where each hospital maintains its own database or on a cloud approach where the health records are stored in a cloud server and managed by a third-party cloud service provider. However, these approaches suffer from the issues of security, privacy, data vulnerability and fragmentation. Furthermore, healthcare providers and patients are unable to have a unified view of a patient's medical history from all visited medical care centers. This results in additional treatment costs, repeated medical tests and increased time to diagnosis. The data traceability, immutability, transparency, replication, security and privacy traits of the emerging blockchain technology have a promising potential in the healthcare domain addressing these issues. In this paper, we propose BlockHR, a patient-centric healthcare records management system for efficient medical care at an optimal cost. The system enables healthcare providers to enter the patients' medical record data to the blockchain network and allows patients to enter their social data such as sleeping habits, physical activities, and current location. Consequently, BlockHR provides support to doctors for better diagnosis and prognosis. We evaluate the performance of BlockHR in terms of execution time and the total amount of data transferred for ledger update with an increasing number of hospitals and blocks in the network.
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TL;DR: In this paper, the authors provide an in-depth analysis of the blockchain-cloud integration for the healthcare system to give the readers the motivations behind the emergence of this new paradigm, introduce a classification of existing architectures and their applications for better healthcare, and highlight the research challenges for the integrated BcC architecture.
Abstract: Blockchain is a disruptive technology for shaping the next era of a healthcare system striving for efficient and effective patient care. This is thanks to its peer-to-peer, secure, and transparent characteristics. On the other hand, cloud computing made its way into the healthcare system thanks to its elasticity and cost-efficiency nature. However, cloud-based systems fail to provide a secured and private patient-centric cohesive view to multiple healthcare stakeholders. In this situation, blockchain provides solutions to address security and privacy concerns of the cloud because of its decentralization feature combined with data security and privacy, while cloud provides solutions to the blockchain scalability and efficiency challenges. Therefore a novel paradigm of blockchain-cloud integration (BcC) emerges for the domain of healthcare. In this paper, we provide an in-depth analysis of the BcC integration for the healthcare system to give the readers the motivations behind the emergence of this new paradigm, introduce a classification of existing architectures and their applications for better healthcare. We then review the development platforms and services and highlight the research challenges for the integrated BcC architecture, possible solutions, and future research directions. The results of this paper will be useful for the healthcare industry to design and develop a data management system for better patient care.
20 citations
TL;DR: The SLR found that blockchain technology promises to provide decentralization, security, and privacy that traditional EHRs often lack and would provide potential researchers with the type of blockchain for future research.
Abstract: Electronic Health Records (EHRs) are electronically-stored health information in a digital format. EHRs are typically shared among healthcare stakeholders and face power failure, data misuse, lack of privacy, security, and audit trail. On the other hand, blockchain is the revolutionary invention of the twentieth century that offers a distributed and decentralized setting to communicate among nodes in a list of networks without a central authority. It can address the limitations of EHRs management and provide a safer, secured, and decentralized environment for exchanging EHRs data. Three categories of blockchain-based potential solutions have been proposed by researchers to handle EHRs: conceptual, prototype, and implemented. This study focused on a Systematic Literature Review (SLR) to find and analyze articles submitted either conceptual or implemented to manage EHRs using blockchain. The study examined 99 papers that were collected from various publication categories. The deep technical analysis focused on evaluating articles based on privacy, security, scalability, accessibility, cost, consensus algorithms, and the type of blockchain used. The SLR found that blockchain technology promises to provide decentralization, security, and privacy that traditional EHRs often lack. Moreover, results obtained from the detailed studies would provide potential researchers with the type of blockchain for future research. Finally, future research directions, in the end, would direct enthusiasm to combine new blockchain-based systems to manage EHRs properly.
18 citations
TL;DR: In this paper , a systematic literature review (SLR) was conducted to find and analyze articles submitted either conceptual or implemented to manage EHRs using blockchain, and a deep technical analysis focused on evaluating articles based on privacy, security, scalability, accessibility, cost, consensus algorithms and the type of blockchain used.
Abstract: Electronic Health Records (EHRs) are electronically-stored health information in a digital format. EHRs are typically shared among healthcare stakeholders and face power failure, data misuse, lack of privacy, security, and audit trail. On the other hand, blockchain is the revolutionary invention of the twentieth century that offers a distributed and decentralized setting to communicate among nodes in a list of networks without a central authority. It can address the limitations of EHRs management and provide a safer, secured, and decentralized environment for exchanging EHRs data. Three categories of blockchain-based potential solutions have been proposed by researchers to handle EHRs: conceptual, prototype, and implemented. This study focused on a Systematic Literature Review (SLR) to find and analyze articles submitted either conceptual or implemented to manage EHRs using blockchain. The study examined 99 papers that were collected from various publication categories. The deep technical analysis focused on evaluating articles based on privacy, security, scalability, accessibility, cost, consensus algorithms, and the type of blockchain used. The SLR found that blockchain technology promises to provide decentralization, security, and privacy that traditional EHRs often lack. Moreover, results obtained from the detailed studies would provide potential researchers with the type of blockchain for future research. Finally, future research directions, in the end, would direct enthusiasm to combine new blockchain-based systems to manage EHRs properly.
17 citations
TL;DR: A taxonomy of the technology-enabled smart city applications’ systems is provided and insights into those systems are presented for the realization of a trustworthy and efficient smart city ecosystem.
Abstract: The recent upsurge of smart cities’ applications and their building blocks in terms of the Internet of Things (IoT), Artificial Intelligence (AI), federated and distributed learning, big data analytics, blockchain, and edge-cloud computing has urged the design of the upcoming 6G network generation, due to their stringent requirements in terms of the quality of services (QoS), availability, and dependability to satisfy a Service-Level-Agreement (SLA) for the end users. Industries and academia have started to design 6G networks and propose the use of AI in its protocols and operations. Published papers on the topic discuss either the requirements of applications via a top-down approach or the network requirements in terms of agility, performance, and energy saving using a down-top perspective. In contrast, this paper adopts a holistic outlook, considering the applications, the middleware, the underlying technologies, and the 6G network systems towards an intelligent and integrated computing, communication, coordination, and decision-making ecosystem. In particular, we discuss the temporal evolution of the wireless network generations’ development to capture the applications, middleware, and technological requirements that led to the development of the network generation systems from 1G to AI-enabled 6G and its employed self-learning models. We provide a taxonomy of the technology-enabled smart city applications’ systems and present insights into those systems for the realization of a trustworthy and efficient smart city ecosystem. We propose future research directions in 6G networks for smart city applications.
9 citations
TL;DR: In this paper , the authors proposed an IoT-edge-Artificial Intelligence (AI)-blockchain system for diabetes prediction based on risk factors, which is underpinned by the blockchain to obtain a cohesive view of the risk factors data from patients across different hospitals and to ensure security and privacy of the user's data.
Abstract: Diabetes Mellitus, one of the leading causes of death worldwide, has no cure till date and can lead to severe health complications, such as retinopathy, limb amputation, cardiovascular diseases, and neuronal disease, if left untreated. Consequently, it becomes crucial to take precautionary measures to avoid/predict the occurrence of diabetes. Machine learning approaches have been proposed and evaluated in the literature for diabetes prediction. This paper proposes an IoT-edge-Artificial Intelligence (AI)-blockchain system for diabetes prediction based on risk factors. The proposed system is underpinned by the blockchain to obtain a cohesive view of the risk factors data from patients across different hospitals and to ensure security and privacy of the user’s data. Furthermore, we provide a comparative analysis of different medical sensors, devices, and methods to measure and collect the risk factors values in the system. Numerical experiments and comparative analysis were carried out between our proposed system, using the most accurate random forest (RF) model, and the two most used state-of-the-art machine learning approaches, Logistic Regression (LR) and Support Vector Machine (SVM), using three real-life diabetes datasets. The results show that the proposed system using RF predicts diabetes with 4.57% more accuracy on average compared to LR and SVM, with 2.87 times more execution time. Data balancing without feature selection does not show significant improvement. The performance is improved by 1.14% and 0.02% after feature selection for PIMA Indian and Sylhet datasets respectively, while it reduces by 0.89% for MIMIC III.
2 citations
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"Performance Evaluation of a Patient..." refers methods in this paper
...Consequently, the execution time and the amount of data transferred for ledger update with increasing number of blocks is more than with the increasing number of hospitals The experimental results reveal that the use of PBFT consensus algorithm is not efficient for health-based blockchain....
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...The selection of PBFT over the popular Proof of Work [3] is due to the low energy consumption and better performance of the former [18, 30]....
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...For the PBFT protocol to function properly, the number of malicious or crashed nodes in the network must always be less than n/3, where n is the total number of nodes....
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...We use PBFT which, compared to PoW, consumes less energy for a permissioned blockchain network [17]....
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...The consensus protocol used in BlockHR is PBFT [10, 29]....
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1,860 citations
01 Aug 2016
TL;DR: This paper proposes MedRec: a novel, decentralized record management system to handle EMRs, using blockchain technology, and incentivizes medical stakeholders to participate in the network as blockchain “miners”, enabling the emergence of data economics.
Abstract: Years of heavy regulation and bureaucratic inefficiency have slowed innovation for electronic medical records (EMRs). We now face a critical need for such innovation, as personalization and data science prompt patients to engage in the details of their healthcare and restore agency over their medical data. In this paper, we propose MedRec: a novel, decentralized record management system to handle EMRs, using blockchain technology. Our system gives patients a comprehensive, immutable log and easy access to their medical information across providers and treatment sites. Leveraging unique blockchain properties, MedRec manages authentication, confidentiality, accountability and data sharing -- crucial considerations when handling sensitive information. A modular design integrates with providers' existing, local data storage solutions, facilitating interoperability and making our system convenient and adaptable. We incentivize medical stakeholders (researchers, public health authorities, etc.) to participate in the network as blockchain "miners". This provides them with access to aggregate, anonymized data as mining rewards, in return for sustaining and securing the network via Proof of Work. MedRec thus enables the emergence of data economics, supplying big data to empower researchers while engaging patients and providers in the choice to release metadata. The purpose of this short paper is to expose, prior to field tests, a working prototype through which we analyze and discuss our approach.
1,578 citations
"Performance Evaluation of a Patient..." refers background in this paper
...However, very few works [2, 13, 14, 19, 32, 35, 45, 55, 57, 60] propose a health information system using blockchain for sharing patients’ medical records among different hospitals....
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TL;DR: An App (called Healthcare Data Gateway (HGD) architecture based on blockchain is proposed to enable patient to own, control and share their own data easily and securely without violating privacy, which provides a new potential way to improve the intelligence of healthcare systems while keeping patient data private.
Abstract: Healthcare data are a valuable source of healthcare intelligence. Sharing of healthcare data is one essential step to make healthcare system smarter and improve the quality of healthcare service. Healthcare data, one personal asset of patient, should be owned and controlled by patient, instead of being scattered in different healthcare systems, which prevents data sharing and puts patient privacy at risks. Blockchain is demonstrated in the financial field that trusted, auditable computing is possible using a decentralized network of peers accompanied by a public ledger. In this paper, we proposed an App (called Healthcare Data Gateway (HGD)) architecture based on blockchain to enable patient to own, control and share their own data easily and securely without violating privacy, which provides a new potential way to improve the intelligence of healthcare systems while keeping patient data private. Our proposed purpose-centric access model ensures patient own and control their healthcare data; simple unified Indicator-Centric Schema (ICS) makes it possible to organize all kinds of personal healthcare data practically and easily. We also point out that MPC (Secure Multi-Party Computing) is one promising solution to enable untrusted third-party to conduct computation over patient data without violating privacy.
884 citations
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810 citations
"Performance Evaluation of a Patient..." refers background in this paper
...The selection of PBFT over the popular Proof of Work [3] is due to the low energy consumption and better performance of the former [18, 30]....
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