The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Healthcare Data Gateways: Found Healthcare Intelligence on Blockchain with Novel Privacy Risk Control
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.
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In the citing paper
“However, there has been no study to evaluate the use of blockchain technology in an mHealth system.”
From Tamper-Resistant Mobile Health Using Blockchain Technology. (2017) · cites this paper as [12]
In the citing paper
“Further, blockchain may assist in creating a viable information ecosystem for managing such PHRs (Mamoshina et al., 2018) by incorporating heterogeneous forms of data (Yue et al., 2016;Shen et al., 2019;Silva et al., 2019), including medical big data (Kaur et al., 2018).”
From Blockchain in healthcare: A systematic literature review, synthesizing framework and future research agenda (2020) · cites this paper as Yue et al., 2016
In the citing paper
“Our review suggests that few studies have acknowledged the need for regulatory compliance (Yue et al., 2016) or even the standards and goals for compliance requirements (Zhang & Lin, 2018;Al Omar et al., 2019;Li et al., 2019).”
From Blockchain in healthcare: A systematic literature review, synthesizing framework and future research agenda (2020) · cites this paper as Yue et al., 2016
In the citing paper
“These concerns are mainly related to the technical limitations of blockchain technology, such as the security of individual nodes (Griggs et al., 2018), the level of security enabled by the cryptographic elements incorporated in framework (Tian et al., 2019), and the maintenance of data privacy while requesters complete their computations (Yue et al., 2016).”
From Blockchain in healthcare: A systematic literature review, synthesizing framework and future research agenda (2020) · cites this paper as Yue et al., 2016
In the citing paper
“If the accessibility of knowledge or data becomes seamless through expanded Software and Applications and mobile devices, patients gain access to their medical history and details regarding care (Yue et al. 2016).”
From Blockchain and Artificial Intelligence Technology in E-Health (2021) · cites this paper as Yue et al. 2016
Citations
Cites
Multidimensional binary search trees used for associative searching
Bentley, J. L. (1975) · Communications of the ACM · doi:10.1145/361002.361007 · Cited by 7,498
Guttman, A. (1984) · ACM SIGMOD International Conference on Management of Data (SIGMOD) · doi:10.1145/602259.602266 · Cited by 6,679
Goldreich, O., Micali, S., & Wigderson, A. (1987) · Proceedings of the nineteenth annual ACM conference on Theory of computing - STOC '87 · doi:10.1145/28395.28420 · Cited by 3,590
Multiparty unconditionally secure protocols
Chaum, D., Crépeau, C., & Damgård, I. (1988) · ACM Symposium on Theory of Computing (STOC) · doi:10.1145/62212.62214 · Cited by 1,554
Health-CPS: Healthcare Cyber-Physical System Assisted by Cloud and Big Data
Zhang⋆, Y., Meikang Qiu, A., Tsai, C., Hassan, M. M., & Alamri, A. M. (2015) · IEEE Systems Journal · doi:10.1109/jsyst.2015.2460747 · Cited by 927
Enigma: Decentralized Computation Platform with Guaranteed Privacy
Zyskind, G., & Pentland, A. (2018) · The MIT Press eBooks · doi:10.7551/mitpress/11636.003.0018 · Cited by 467
A Cloud Computing Solution for Patient's Data Collection in Health Care Institutions
Rolim, C. O., Koch, F. L., Westphall, C. B., Werner, J., Fracalossi, A., & Salvador, G. S. (2010) · International Conference on eHealth, Telemedicine, and Social Medicine · doi:10.1109/etelemed.2010.19 · Cited by 413
Data Mining in Healthcare – A Review
Jothi, N., Rashid, N. A., & Husain, W. (2015) · Procedia Computer Science · doi:10.1016/j.procs.2015.12.145 · Cited by 305
Privacy preserving EHR system using attribute-based infrastructure
Narayan, S., Gagné, M., & Safavi-Naini, R. (2010) · Proceedings of the 2010 ACM workshop on Cloud computing security workshop · doi:10.1145/1866835.1866845 · Cited by 257
Zhang⋆, Y., Chen, M., Huang, D., Wu, D., & Li, Y. (2016) · Future Generation Computer Systems · doi:10.1016/j.future.2015.12.001 · Cited by 244
ESPAC: Enabling Security and Patient-centric Access Control for eHealth in cloud computing
Barua, M., Liang, X., Lu, R., & Shen, X. (2011) · International Journal of Security and Networks · doi:10.1504/ijsn.2011.043666 · Cited by 146
Zhang⋆, Y. (2016) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2016.2592520 · Cited by 111
Chen, M., Zhang⋆, Y., Hu, L., Taleb, T., & Sheng, Z. (2015) · Mobile Networks and Applications · doi:10.1007/s11036-015-0590-7 · Cited by 110
Novel Data Protection Model in Healthcare Cloud
Chen, L., & Hoang, D. B. (2011) · IEEE International Conference on High Performance Computing and Communications (HPCC) · doi:10.1109/hpcc.2011.148 · Cited by 53
Framework of a national level electronic health record system
Gul, O., Al‐Qutayri, M., Yeun, C. Y., & Vu, Q. H. (2012) · International Conference on Cloud Computing Technologies, Applications and Management (ICCCTAM) · doi:10.1109/iccctam.2012.6488072 · Cited by 48
Optimizing R-tree for flash memory
Jin, P., Xie, X., Wang, N., & Yue, L. (2015) · Expert Systems with Applications · doi:10.1016/j.eswa.2015.01.011 · Cited by 27
Patra, M. R., Das, R. K., & Padhy, R. P. (2012) · International Conference on Theory and Practice of Electronic Governance · doi:10.1145/2463728.2463805 · Cited by 27
CloudHealth: Developing a reliable cloud platform for healthcare applications
Hendrick, E. C., Schooley, B., & Gao, C. (2013) · IEEE Consumer Communications and Networking Conference · doi:10.1109/ccnc.2013.6488579 · Cited by 25
Quad-kd trees: A general framework for kd trees and quad trees
Bereczky, N., Duch, A., Németh, K., & Roura, S. (2015) · Theoretical Computer Science · doi:10.1016/j.tcs.2015.12.030 · Cited by 21
Kemkar, O. S., & Dahikar, P. B. (2012) · Cited by 11
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Casino, F., Dasaklis, T. K., & Patsakis, C. (2018) · Telematics and Informatics · doi:10.1016/j.tele.2018.11.006 · Cited by 2,954
A Survey on the Security of Blockchain Systems
Li, X., Jiang, P., Chen, T., Luo, X., & Wen, Q. (2020) · Future Generation Computer Systems · doi:10.1016/j.future.2017.08.020 · Cited by 1,772
Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers
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Blockchain distributed ledger technologies for biomedical and health care applications
Kuo, T.-T., Kim, H.-E., & Ohno-Machado, L. (2017) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocx068 · Cited by 1,350
Blockchain technology in healthcare: a systematic review
Agbo, C. C., Mahmoud, Q. H., & Eklund, J. M. (2019) · Healthcare · doi:10.3390/healthcare7020056 · Cited by 1,131
Metadata
- Authors
- Yue, X., Wang, H., Jin, D., Li, M., & Jiang, W.
- Affiliations
- Zhongnan University of Economics and Law (CN)
- Corresponding author
- Wang, Huiju
- Venue
- Journal of Medical Systems
- Published
- 2016-08-26
- Volume
- 40
- Issue
- 10
- Pages
- 218-218
- ISSN
- 0148-5598 (ISSN-L)
- 1573-689X
- OpenAlex
- W2514994441
- Cited by
- 1,240
- References
- 20
- Citations by year
- 2026: 38 · 2025: 95 · 2024: 106 · 2023: 139 · 2022: 177 · 2021: 196 · 2020: 168 · 2019: 188 · 2018: 101 · 2017: 25 · 2016: 7
- FWCI
- 239.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Medical Systems (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Keywords
- health data sharing, blockchain, patient data ownership, data privacy, secure multi-party computation, decentralized data management
- MeSH terms
- Confidentiality, Humans, Risk Management, Computer Security, Information Dissemination, Electronic Health Records
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