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      A Survey of Blockchain-Based Strategies for Healthcare

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          Abstract

          Blockchain technology has been gaining visibility owing to its ability to enhance the security, reliability, and robustness of distributed systems. Several areas have benefited from research based on this technology, such as finance, remote sensing, data analysis, and healthcare. Data immutability, privacy, transparency, decentralization, and distributed ledgers are the main features that make blockchain an attractive technology. However, healthcare records that contain confidential patient data make this system very complicated because there is a risk of a privacy breach. This study aims to address research into the applications of the blockchain healthcare area. It sets out by discussing the management of medical information, as well as the sharing of medical records, image sharing, and log management. We also discuss papers that intersect with other areas, such as the Internet of Things, the management of information, tracking of drugs along their supply chain, and aspects of security and privacy. As we are aware that there are other surveys of blockchain in healthcare, we analyze and compare both the positive and negative aspects of their papers. Finally, we seek to examine the concepts of blockchain in the medical area, by assessing their benefits and drawbacks and thus giving guidance to other researchers in the area. Additionally, we summarize the methods used in healthcare per application area and show their pros and cons.

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          Most cited references101

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          k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY

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            Systematic review: impact of health information technology on quality, efficiency, and costs of medical care.

            Experts consider health information technology key to improving efficiency and quality of health care. To systematically review evidence on the effect of health information technology on quality, efficiency, and costs of health care. The authors systematically searched the English-language literature indexed in MEDLINE (1995 to January 2004), the Cochrane Central Register of Controlled Trials, the Cochrane Database of Abstracts of Reviews of Effects, and the Periodical Abstracts Database. We also added studies identified by experts up to April 2005. Descriptive and comparative studies and systematic reviews of health information technology. Two reviewers independently extracted information on system capabilities, design, effects on quality, system acquisition, implementation context, and costs. 257 studies met the inclusion criteria. Most studies addressed decision support systems or electronic health records. Approximately 25% of the studies were from 4 academic institutions that implemented internally developed systems; only 9 studies evaluated multifunctional, commercially developed systems. Three major benefits on quality were demonstrated: increased adherence to guideline-based care, enhanced surveillance and monitoring, and decreased medication errors. The primary domain of improvement was preventive health. The major efficiency benefit shown was decreased utilization of care. Data on another efficiency measure, time utilization, were mixed. Empirical cost data were limited. Available quantitative research was limited and was done by a small number of institutions. Systems were heterogeneous and sometimes incompletely described. Available financial and contextual data were limited. Four benchmark institutions have demonstrated the efficacy of health information technologies in improving quality and efficiency. Whether and how other institutions can achieve similar benefits, and at what costs, are unclear.
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              The Algorithmic Foundations of Differential Privacy

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                Author and article information

                Journal
                ACM Computing Surveys
                ACM Comput. Surv.
                Association for Computing Machinery (ACM)
                0360-0300
                1557-7341
                July 2020
                July 2020
                : 53
                : 2
                : 1-27
                Affiliations
                [1 ]University of São Paulo, Brazil
                [2 ]University of Southern California, Los Angeles, CA
                Article
                10.1145/3376915
                60df5b37-643f-4a84-95c3-c8998c41d4de
                © 2020
                History

                Quantitative & Systems biology,Biophysics
                Quantitative & Systems biology, Biophysics

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