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A Systematic Review of the Adoption of Blockchain for Supply Chain Processes. JOURNAL OF GLOBAL INFORMATION MANAGEMENT 2022. [DOI: 10.4018/jgim.297625] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
This paper systematically reviews the literature on the adoption of Blockchain technology in Supply Chain Management (SCM) processes. Using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) methodology, 53 peer-reviewed research publications from five different databases (IEEE Xplore, Science Direct, Scopus, Google Scholar, and EBSCOhost) were selected and analyzed using a classification coding framework. The findings reveal that Agri-food traceability, Blockchain security, smart contracts, and the Internet of Things (IoT) were the significant identified current trends in the use of Blockchain in SCM processes. The key identified challenges include high costs of transactions and a lack of trust between stakeholders. Identified solutions were Blockchain traceability systems and the use of smart contracts and IoTs. In addition, this paper identified gaps in the literature that need to be addressed in future studies.
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Zhuang Y, Zhang L, Gao X, Shae ZY, Tsai JJP, Li P, Shyu CR. Re-engineering a Clinical Trial Management System Using Blockchain Technology: System Design, Development, and Case Studies. J Med Internet Res 2022; 24:e36774. [PMID: 35759315 PMCID: PMC9274392 DOI: 10.2196/36774] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 05/07/2022] [Accepted: 05/20/2022] [Indexed: 11/13/2022] Open
Abstract
Background A clinical trial management system (CTMS) is a suite of specialized productivity tools that manage clinical trial processes from study planning to closeout. Using CTMSs has shown remarkable benefits in delivering efficient, auditable, and visualizable clinical trials. However, the current CTMS market is fragmented, and most CTMSs fail to meet expectations because of their inability to support key functions, such as inconsistencies in data captured across multiple sites. Blockchain technology, an emerging distributed ledger technology, is considered to potentially provide a holistic solution to current CTMS challenges by using its unique features, such as transparency, traceability, immutability, and security. Objective This study aimed to re-engineer the traditional CTMS by leveraging the unique properties of blockchain technology to create a secure, auditable, efficient, and generalizable CTMS. Methods A comprehensive, blockchain-based CTMS that spans all stages of clinical trials, including a sharable trial master file system; a fast recruitment and simplified enrollment system; a timely, secure, and consistent electronic data capture system; a reproducible data analytics system; and an efficient, traceable payment and reimbursement system, was designed and implemented using the Quorum blockchain. Compared with traditional blockchain technologies, such as Ethereum, Quorum blockchain offers higher transaction throughput and lowers transaction latency. Case studies on each application of the CTMS were conducted to assess the feasibility, scalability, stability, and efficiency of the proposed blockchain-based CTMS. Results A total of 21.6 million electronic data capture transactions were generated and successfully processed through blockchain, with an average of 335.4 transactions per second. Of the 6000 patients, 1145 were matched in 1.39 seconds using 10 recruitment criteria with an automated matching mechanism implemented by the smart contract. Key features, such as immutability, traceability, and stability, were also tested and empirically proven through case studies. Conclusions This study proposed a comprehensive blockchain-based CTMS that covers all stages of the clinical trial process. Compared with our previous research, the proposed system showed an overall better performance. Our system design, implementation, and case studies demonstrated the potential of blockchain technology as a potential solution to CTMS challenges and its ability to perform more health care tasks.
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Affiliation(s)
- Yan Zhuang
- National Institute of Health Data Science, Peking University, Beijing, China.,Advanced Institute of Information Technology, Peking University, Hangzhou, China
| | - Luxia Zhang
- National Institute of Health Data Science, Peking University, Beijing, China.,Advanced Institute of Information Technology, Peking University, Hangzhou, China
| | - Xiyuan Gao
- Department of Statistics, University of Missouri, Columbia, MO, United States
| | - Zon-Yin Shae
- Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan
| | - Jeffrey J P Tsai
- Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan
| | - Pengfei Li
- Advanced Institute of Information Technology, Peking University, Hangzhou, China
| | - Chi-Ren Shyu
- Institute for Data Science and Informatics, University of Missouri, Columbia, MO, United States
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Saeed H, Malik H, Bashir U, Ahmad A, Riaz S, Ilyas M, Bukhari WA, Khan MIA. Blockchain technology in healthcare: A systematic review. PLoS One 2022; 17:e0266462. [PMID: 35404955 PMCID: PMC9000089 DOI: 10.1371/journal.pone.0266462] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 03/21/2022] [Indexed: 11/18/2022] Open
Abstract
Blockchain technology (BCT) has emerged in the last decade and added a lot of interest in the healthcare sector. The purpose of this systematic literature review (SLR) is to explore the potential paradigm shift in healthcare utilizing BCT. The study is compiled by reviewing research articles published in nine well-reputed venues such as IEEE Xplore, ACM Digital Library, Springs Link, Scopus, Taylor & Francis, Science Direct, PsycINFO, Ovid Medline, and MDPI between January 2016 to August 2021. A total of 1,192 research studies were identified out of which 51 articles were selected based on inclusion criteria for this SLR that presents the modern information on the recent implications and gaps in the use of BCT for enhancing the healthcare procedures. According to the outcomes, BCT is being applied to design the novel and advanced interventions to enrich the current protocol of managing, distributing, and processing clinical records and personal medical information. BCT is enduring the conceptual development in the healthcare domain, where it has summed up the substantial elements through better and enhanced efficiency, technological innovation, access control, data privacy, and security. A framework is developed to address the probable field where future researchers can add considerable value, such as data protection, system architecture, and regulatory compliance. Finally, this SLR concludes that the upcoming research can support the pervasive implementation of BCT to address the critical dilemmas related to health diagnostics, enhancing the patient healthcare process in remote monitoring or emergencies, data integrity, and avoiding fraud.
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Affiliation(s)
- Huma Saeed
- Department of Computer Science, National College of Business Administration & Economics Lahore, Multan, Pakistan
| | - Hassaan Malik
- Department of Computer Science, National College of Business Administration & Economics Lahore, Multan, Pakistan
- Department of Computer Science, University of Management and Technology, Lahore, Pakistan
- * E-mail:
| | - Umair Bashir
- Department of Computer Science, National College of Business Administration & Economics Lahore, Multan, Pakistan
| | - Aiesha Ahmad
- Department of Computer Science, National College of Business Administration & Economics Lahore, Multan, Pakistan
| | - Shafia Riaz
- Department of Computer Science, National College of Business Administration & Economics Lahore, Multan, Pakistan
| | - Maheen Ilyas
- Department of Computer Science, National College of Business Administration & Economics Lahore, Multan, Pakistan
| | - Wajahat Anwaar Bukhari
- Department of Computer Science, National College of Business Administration & Economics Lahore, Multan, Pakistan
| | - Muhammad Imran Ali Khan
- Department of Computer Science, National College of Business Administration & Economics Lahore, Multan, Pakistan
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Omidian H, Omidi Y. Blockchain in Pharmaceutical Life Cycle Management. Drug Discov Today 2022; 27:935-938. [DOI: 10.1016/j.drudis.2022.01.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 01/14/2022] [Accepted: 01/31/2022] [Indexed: 11/15/2022]
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Cheng ASK, Guan Q, Su Y, Zhou P, Zeng Y. Integration of Machine Learning and Blockchain Technology in the Healthcare Field: A Literature Review and Implications for Cancer Care. Asia Pac J Oncol Nurs 2021; 8:720-724. [PMID: 34790856 PMCID: PMC8522602 DOI: 10.4103/apjon.apjon-2140] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 08/04/2021] [Indexed: 11/04/2022] Open
Abstract
This brief report aimed to describe a narrative review about the application of machine learning (ML) methods and Blockchain technology (BCT) in the healthcare field, and to illustrate the integration of these two technologies in cancer survivorship care. A total of six eligible papers were included in the narrative review. ML and BCT are two data-driven technologies, and there is rapidly growing interest in integrating them for clinical data management and analysis in healthcare. The findings of this report indicate that both technologies can integrate feasibly and effectively. In conclusion, this brief report provided the state-of-art evidence about the integration of the most promising technologies of ML and BCT in health field, and gave an example of how to apply these two most disruptive technologies in cancer survivorship care.
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Affiliation(s)
- Andy S K Cheng
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China
| | - Qiongyao Guan
- Department of Nursing, Yunnan Cancer Hospital, Kunming, China
| | - Yan Su
- Department of Nursing, Yunnan Cancer Hospital, Kunming, China
| | - Ping Zhou
- Department of Oncology, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Yingchun Zeng
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China
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Purohit S, Calyam P, Alarcon ML, Bhamidipati NR, Mosa A, Salah K. HonestChain: Consortium blockchain for protected data sharing in health information systems. PEER-TO-PEER NETWORKING AND APPLICATIONS 2021; 14:3012-3028. [PMID: 33968293 PMCID: PMC8092970 DOI: 10.1007/s12083-021-01153-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 04/02/2021] [Indexed: 05/05/2023]
Abstract
Healthcare innovations are increasingly becoming reliant on high variety and standards-compliant (e.g., HIPAA, common data model) distributed data sets that enable predictive analytics. Consequently, health information systems need to be developed using cooperation and distributed trust principles to allow protected data sharing between multiple domains or entities (e.g., health data service providers, hospitals and research labs). In this paper, we present a novel health information sharing system viz., HonestChain that uses Blockchain technology to allow organizations to have incentive-based and trustworthy cooperation to either access or provide protected healthcare records. More specifically, we use a consortium Blockchain approach coupled with chatbot guided interfaces that allow data requesters to: (a) comply with data access standards, and (b) allow them to gain reputation in a consortium. We also propose a reputation scheme for creation and sustenance of the consortium with peers using Requester Reputation and Provider Reputation metrics. We evaluate HonestChain using Hyperledger Composer in a realistic simulation testbed on a public cloud infrastructure. Our results show that our HonestChain performs better than the state-of-the-art requester reputation schemes for data request handling, while choosing the most appropriate provider peers. We particularly show that HonestChain achieves a better tradeoff in metrics such as service time and request resubmission rate. Additionally, we also demonstrate the scalability of our consortium platform in terms of the Blockchain transaction times.
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Affiliation(s)
| | | | | | | | - Abu Mosa
- University of Missouri-Columbia, Columbia, MO USA
| | - Khaled Salah
- University of Missouri-Columbia, Columbia, MO USA
- Khalifa University, Abu Dhabi, UAE
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Senbekov M, Saliev T, Bukeyeva Z, Almabayeva A, Zhanaliyeva M, Aitenova N, Toishibekov Y, Fakhradiyev I. The Recent Progress and Applications of Digital Technologies in Healthcare: A Review. Int J Telemed Appl 2020; 2020:8830200. [PMID: 33343657 PMCID: PMC7732404 DOI: 10.1155/2020/8830200] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 11/16/2020] [Accepted: 11/17/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The implementation of medical digital technologies can provide better accessibility and flexibility of healthcare for the public. It encompasses the availability of open information on the health, treatment, complications, and recent progress on biomedical research. At present, even in low-income countries, diagnostic and medical services are becoming more accessible and available. However, many issues related to digital health technologies remain unmet, including the reliability, safety, testing, and ethical aspects. PURPOSE The aim of the review is to discuss and analyze the recent progress on the application of big data, artificial intelligence, telemedicine, block-chain platforms, smart devices in healthcare, and medical education. Basic Design. The publication search was carried out using Google Scholar, PubMed, Web of Sciences, Medline, Wiley Online Library, and CrossRef databases. The review highlights the applications of artificial intelligence, "big data," telemedicine and block-chain technologies, and smart devices (internet of things) for solving the real problems in healthcare and medical education. Major Findings. We identified 252 papers related to the digital health area. However, the number of papers discussed in the review was limited to 152 due to the exclusion criteria. The literature search demonstrated that digital health technologies became highly sought due to recent pandemics, including COVID-19. The disastrous dissemination of COVID-19 through all continents triggered the need for fast and effective solutions to localize, manage, and treat the viral infection. In this regard, the use of telemedicine and other e-health technologies might help to lessen the pressure on healthcare systems. Summary. Digital platforms can help optimize diagnosis, consulting, and treatment of patients. However, due to the lack of official regulations and recommendations, the stakeholders, including private and governmental organizations, are facing the problem with adequate validation and approbation of novel digital health technologies. In this regard, proper scientific research is required before a digital product is deployed for the healthcare sector.
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Affiliation(s)
- Maksut Senbekov
- S.D. Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan
| | - Timur Saliev
- S.D. Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan
| | | | | | | | - Nazym Aitenova
- NJSC “Astana Medical University”, Nur-Sultan, Kazakhstan
| | | | - Ildar Fakhradiyev
- S.D. Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan
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