Blockchain in Healthcare - Part Two

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This blog is a continuation of the previous blog titled 'Blockchain in Healthcare - Part One'. We will look further at the applications of blockchain technology in the healthcare space.

Privacy 

We will shift our emphasis to privacy; Zhang and Lin [83] propose a blockchain-based secure and privacy-preserving EMR scheme which uses private and consortium blockchains to store the actual EMR and the pointers to the EMR respectively. This scheme also relies on asymmetric encryption but also implements mechanisms for conformance testing to ensure the system’s availability. 

In [65], the authors propose a privacy-preserving platform, MediBchain that employs cryptographic functions to de-identify patients’ data in blockchain-based EMR systems. 

Yeu et al. in [58] also propose an architecture called Healthcare Data Gateway (HDG) for blockchain-based EMR application which allows patients to own, control and choose how to share their data in a privacy-preserving manner. A related architecture is proposed for the management and sharing of medical data of diabetes patients using multi-signature blockchain contracts to achieve access control and data privacy [59]. 

Drug/Pharmaceutical Supply Chain

One other identified use case of blockchain is in health supply chain management, particularly in the drug/pharmaceutical industry. The delivery of counterfeit or substandard medications can have dire consequences for the patients, yet this is a common problem faced in the pharmaceutical industry. Blockchain technology has been identified as having the capability to address this problem [13,15,55,56,74].

Engelhardt, in his survey, mentions some companies that are working on how blockchain can be used to detect prescription drug fraud. The companies mentioned include Nuco, HealthChainRx and Scalamed [14]. The general idea is to record every transaction relating to the prescription of drugs on the blockchain network to which all the stakeholders (manufacturers, distributors, doctors, patients and pharmacists) are connected. This way, any alteration or malicious modification of the prescription by any of the parties can be detected. Mettler also mentions the Counterfeit Medicines Project that is launched by Hyperledger (the developers of Hyperledger Fabric [12]) to combat drug counterfeiting. 

Here is an implementation of an example blockchain-based application for pharmaceutical supply chain management. Modum.io AG is a startup that uses blockchain to achieve data immutability while creating public accessibility of the temperature records of pharmaceutical products during their transportation so that their compliance to quality control temperature requirements can be verified [47]. Mackey and Nayyar, however, report that they found from grey literature many examples of prototypes and research initiatives related to the application of blockchain in the area of pharmaceutical supply chain management [31]. This indicates that industrial players may have released many commercial blockchain-based products to combat the fake medicine trade even when there are still limited academic publications on the subject.

Biomedical Research and Education

Blockchain has an interesting use case in biomedical research and education. In clinical trials, blockchain can help to eliminate falsification of data and the under-reporting or exclusion of undesirable results of clinical research [41,73,74,82]. Blockchain makes it easier for patients to grant permission for their data to be used for clinical trials because of the anonymisation that is inherently encoded in the data [55]. Additionally, the immutability property of blockchain certifies the integrity of data collected through blockchain for clinical study. The transparent and public nature of blockchain also make it easier to replicate research from blockchain-based data. 

All these are some of the reasons blockchain is expected to revolutionise biomedical research [14,17]. Blockchain has also been noted to have the potential to revolutionise the peer-review process for clinical research publications based on its decentralised, immutable and transparent properties [17]. 

Another potential application of blockchain to health professions education (HPE) is presented in [43] where Funk et al. make a case for using blockchain to build an HPE system that will be value-based, competency-based and offer credentialing services without relying on a third-party. A proof of concept implementation of consent traceability in clinical trial using blockchain protocol is presented in [38]. 

Similarly, Nugent et al. present their research in [60] in which they demonstrate how smart contracts on Ethereum blockchain platform can be used to improve data transparency in clinical trials. The Ethereum platform is also used to implement another blockchain-based solution that is proposed to notarize documents retrieved from biomedical databases [71]. 

Remote Patient Monitoring (RPM)

In this Section, we look at how blockchain technology facilitates remote patient monitoring (RPM). Remote patient monitoring involves the collection of biomedical data through body area sensors (or IoT devices) and mobile devices to be able to remotely monitor the status of the patient outside traditional healthcare environments such as the hospital. Blockchain has been proposed as a means for storing, sharing and retrieving the remotely-collected biomedical data [29,32,37].

In [57], Griggs et al. demonstrate how smart contracts on the Ethereum blockchain platform can support real-time patient monitoring application with capability to provide automated interventions in a secure environment. Liang et al. [61] present a Hyperledger-based implementation of blockchain-enabled data collection and sharing among healthcare stakeholders in a mobile healthcare environment. Similarly, blockchain is employed to develop SMEAD, mobile-enabled assisting device for monitoring diabetes patients [79]. 

Another example application is presented in [81] where mobile devices (smartphones) were successfully used to transmit data to a blockchain-based application on Hyperledger Fabric. Ashraf Uddin et al. also developed a blockchain-based patient centric agent (PCA) to achieve end-to-end data security and privacy in a continuous remote patient monitoring application [50]. 

In [75], practical swarm optimization (PSO) is used for root exploit detection and feature optimization in blockchain-based mobile device medical data management. Lastly, Ji et al. proposed a scheme known as BMPLS (Blockchain-based Multi-level Privacy-preserving Location Sharing) for realizing privacy-preserving location sharing for remote monitoring applications.

Health Insurance Claims

Insurance claims processing in healthcare can benefit from blockchain’s transparency, decentralisation, immutability and audit-ability of records stored on it [55]. A number of papers identify insurance claim processing as a very promising area for the application of blockchain in healthcare [13,17,40,55,86]. However, examples of prototype implementations of such systems are very limited. 

One good example we can find is the MIStore (a blockchain-based medical insurance storage system) which is deployed on the Ethereum blockchain platform [70]. Additionally, [14] talks about an initiative by a company named Pokitdok that aims to partner with Intel to build a blockchain-based system that will facilitate insurance claim resolution in healthcare. 

Health Data Analytics (HDA)

Blockchain provides also a unique opportunity to harness the power of other emerging technologies such as deep learning and transfer learning techniques to realise predictive analytics of healthcare data and advance the research in the area of precision medicine [85]. This blockchain use case is also mentioned in [55] and [17], while [51] provides a comprehensive roadmap on how this can be realised. Juneja and Marefat conducted an experimental research in which blockchain is used in a deep-learning architecture for arrhythmia classification [62].

Others

There are other potential areas of application of blockchain in healthcare, including areas such as the dental industry, legal medicine and meaningful use [14,17]. One sets out to identify the metrics for evaluating blockchain-based healthcare applications [69] while the other [80] studies the socio-technical implications of using blockchain technology in healthcare. 

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Further Reading
  1. Nakamoto, S. Bitcoin: A Peer-to-Peer Electronic Cash System. 2008. Available online: www.bitcoin.org 
  2. Swan, M. Blockchain: Blueprint for a New Economy; O’Reilly Media, Inc.: Sebastopol, CA, USA, 2015. 
  3. The Monero Project. Available online: https://getmonero.org/the-monero-project/ 
  4. Dash Official Website|Dash Crypto Currency—Dash. Available online: https://www.dash.org/ 
  5. Litecoin—Open Source P2P Digital Currency. Available online: https://litecoin.org/ 
  6. Ethereum Project. Available online: https://www.ethereum.org/ 
  7. Ethereum Classic—A Smarter Blockchain that Takes Digital Assets Further 2018. Available online: https://ethereumclassic.org/ 
  8. NEO Smart Economy 2018. Available online: https://neo.org/ 
  9. Qtum. 2018. Available online: https://qtum.org/en 
  10. Burniske, C.; Vaughn, E.; Cahana, A.; Shelton, J. How Blockchain Technology Can Enhance Electronic Health Record Operability; Ark Invest: New York, NY, USA, 2016.
  11. Jovanovic, B.; Rousseau, P.L. General Purpose Technologies. In Handbook of Economic Growth; Elsevier: New York, NY, USA, 2005.
  12. Androulaki, E.; Barger, A.; Bortnikov, V.; Cachin, C.; Christidis, K.; De Caro, A.; Enyeart, D.; Ferris, C.; Laventman, G.; Manevich, Y.; et al. Hyperledger Fabric: A Distributed Operating System for Permissioned Blockchains. In Proceedings of the Thirteenth EuroSys Conference; EuroSys ’18; Association for Computing Machinery: New York, NY, USA, 2018; pp. 30:1–30:15.
  13. Angraal, S.; Krumholz, H.M.; Schulz, W.L. Blockchain Technology Applications in Health Care. Circ. Cardiovasc. Qual. Outcomes 2017, 10, e003800. 
  14. Engelhardt, M.A. Hitching Healthcare to the Chain: An Introduction to Blockchain Technology in the Healthcare Sector. Technol. Innov. Manag. Rev. 2017, 7, 22–34. 
  15. Mettler, M. Blockchain Technology in Healthcare the Revolution Starts Here. In Proceedings of the 2016 IEEE 18th International Conference on E-Health Networking, Applications and Services (Healthcom), Munich, Germany, 14–17 September 2016; pp. 520–522. 
  16. Kuo, T.T.; Kim, H.E.; Ohno-Machado, L. Blockchain Distributed Ledger Technologies for Biomedical and Health Care Applications. J. Am. Med. Inform. Assoc. 2017, 24, 1211–1220. 
  17. Roman-Belmonte, J.M.; De la Corte-Rodriguez, H.; Rodriguez-Merchan, E.C.C.; la Corte-Rodriguez, H.; Carlos Rodriguez-Merchan, E. How Blockchain Technology Can Change Medicine. Postgrad. Med. 2018, 130, 420–427. 
  18. Kitchenham, B.; Charters, S. Guidelines for Performing Systematic Literature Reviews in Software Engineering. Engineering 2007, 2, 1051. 
  19. Petersen, K.; Feldt, R.; Mujtaba, S.; Mattsson, M. Systematic Mapping Studies in Software Engineering. In Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering, Bari, Italy, 26–27 June 2008; pp. 68–77. 
  20. Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G.; Altman, D.; Antes, G.; Atkins, D.; Barbour, V.; Barrowman, N.; Berlin, J.A.; et al. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med. 2009, 6. 
  21. Yli-Huumo, J.; Ko, D.; Choi, S.; Park, S.; Smolander, K. Where Is Current Research on Blockchain Technology? A Systematic Review. PLoS ONE 2016, 11, 1–27. 
  22. Hölbl, M.; Kompara, M.; Kamišalić, A.; Zlatolas, L.N. A Systematic Review of the Use of Blockchain in Healthcare. Symmetry 2018, 10, 470. 
  23. Housley, R. Public Key Infrastructure (PKI). In The Internet Encyclopedia; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2004. 
  24. Alhadhrami, Z.; Alghfeli, S.; Alghfeli, M.; Abedlla, J.A.; Shuaib, K. Introducing Blockchains for Healthcare. In Proceedings of the 2017 International Conference on Electrical and Computing Technologies and Applications (ICECTA), Ras Al Khaimah, UAE, 19–21 November 2017; pp. 1–4.
  25. MccCarthy, J. MedStar Attack Found to Be Ransomware, Hackers Demand Bitcoin. 2016. Available online: https://www.healthcareitnews.com/news/medstar-attack-found-be-ransomware-hackers-demand-bitcoin 
  26. Patients and Privacy: GDPR Compliance for Healthcare Organizations—Security News—Trend Micro DK. Available online: https://www.trendmicro.com/vinfo/dk/security/news/online-privacy/patients-and-privacy-gdpr-compliance-for-healthcare-organizations 
  27. Patel, V. A Framework for Secure and Decentralized Sharing of Medical Imaging Data via Blockchain Consensus. Health Inform. J. 2018. 
  28. Hussein, A.F.; ArunKumar, N.; Ramirez-Gonzalez, G.; Abdulhay, E.; Manuel, J.; Tavares, R.S.; Hugo, V.; De Albuquerque, C.; Tavares, J.M.R.S.; de Albuquerque, V.H.C. A Medical Records Managing and Securing Blockchain Based System Supported by a Genetic Algorithm and Discrete Wavelet Transform. Cogn. Syst. Res. 2018, 52, 1–11. 
  29. Dey, T.; Jaiswal, S.; Sunderkrishnan, S.; Katre, N. A Medical Use Case of Internet of Things and Blockchain. In Proceedings of the 2017 International Conference on Intelligent Sustainable Systems (ICISS), Palladam, India, 7–8 December 2017; pp. 486–491. 
  30. Kaur, H.; Alam, M.A.; Jameel, R.; Kumar Mourya, A.; Chang, V.; Alam, M.A.; Jameel, R.; Mourya, A.K.; Chang, V. A Proposed Solution and Future Direction for Blockchain-Based Heterogeneous Medicare Data in Cloud Environment. J. Med. Syst. 2018, 42, 156. 
  31. Mackey, T.K.; Nayyar, G. A Review of Existing and Emerging Digital Technologies to Combat the Global Trade in Fake Medicines. Expert Opin. Drug Saf. 2017, 16, 587–602.
  32. Zhang, J.; Xue, N.; Huang, X. A Secure System for Pervasive Social Network-Based Healthcare. IEEE Access 2017, 4, 9239–9250. 
  33. Liu, W.; Zhu, S.S.; Mundie, T.; Krieger, U. Advanced Block-Chain Architecture for e-Health Systems. In Proceedings of the 2017 IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom), Dalian, China, 12–15 October 2017; pp. 1–6.
  34. Dagher, G.G.; Mohler, J.; Milojkovic, M.; Marella, P.B.; Marella, B. Ancile: Privacy-Preserving Framework for Access Control and Interoperability of Electronic Health Records Using Blockchain Technology. Sustain. Cities Soc. 2018, 39, 283–297. 
  35. Xia, Q.; Sifah, E.B.; Smahi, A.; Amofa, S.; Zhang, X. BBDS: Blockchain-Based Data Sharing for Electronic Medical Records in Cloud Environments. Information 2017, 8, 44. 
  36. Magyar, G. Blockchain: Solving the Privacy and Research Availability Tradeoff for EHR Data: A New Disruptive Technology in Health Data Management. In Proceedings of the 2017 IEEE 30th Neumann Colloquium (NC), Budapest, Hungary, 24–25 November 2017; pp. 135–140.
  37. Weiss, M.; Botha, A.; Herselman, M.; Loots, G. Blockchain as an Enabler for Public MHealth Solutions in South Africa. In Proceedings of the 2017 IST-Africa Week Conference, Windhoek, Namibia, 31 May–2 June 2017; pp. 1–8. 
  38. Benchoufi, M.; Porcher, R.; Ravaud, P. Blockchain Protocols in Clinical Trials: Transparency and Traceability of Consent. F1000 Res. 2017. 
  39. Zhang, X.; Poslad, S. Blockchain Support for Flexible Queries with Granular Access Control to Electronic Medical Records (EMR). In Proceedings of the 2018 IEEE International Conference on Communications (ICC), Kansas City, MO, USA, 20–24 May 2018. 
  40. Gordon, W.J.; Catalini, C. Blockchain Technology for Healthcare: Facilitating the Transition to Patient-Driven Interoperability. Comput. Struct. Biotechnol. J. 2018, 16, 224–230. 
  41. Benchoufi, M.; Ravaud, P. Blockchain Technology for Improving Clinical Research Quality. Trials 2017, 18, 335. 
  42. Ahram, T.; Sargolzaei, A.; Sargolzaei, S.; Daniels, J.; Amaba, B. Blockchain Technology Innovations. In Proceedings of the 2017 IEEE Technology & Engineering Management Conference (TEMSCON), Santa Clara, CA, USA, 8–10 June 2017; pp. 137–141. 
  43. Funk, E.; Riddell, J.; Ankel, F.; Cabrera, D. Blockchain Technology: A Data Framework to Improve Validity, Trust, and Accountability of Information Exchange in Health Professions Education. Acad. Med. 2018, 93, 1791–1794. 
  44. Kamau, G.; Boore, C.; Maina, E.; Njenga, S. Blockchain Technology: Is This the Solution to EMR Interoperability and Security Issues in Developing Countries? In Proceedings of the 2018 IST-Africa Week Conference (IST-Africa), Gaborone, Botswana, 9–11 May 2018; pp. 1–8. 
  45. Esposito, C.; De Santis, A.; Tortora, G.; Chang, H.; Choo, K.-K.R. Blockchain: A Panacea for Healthcare Cloud-Based Data Security and Privacy? IEEE Cloud Comput. 2018, 5, 31–37. 
  46. Li, H.; Zhu, L.; Shen, M.; Gao, F.; Tao, X.; Liu, S. Blockchain-Based Data Preservation System for Medical Data. J. Med Syst. 2018, 42, 141. 
  47. Bocek, T.; Rodrigues, B.B.; Strasser, T.; Stiller, B. Blockchains everywhere—A use-case of blockchains in the pharma supply-chain. In Proceedings of the 2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM), Lisbon, Portugal, 8–12 May 2017; pp. 772–777. 
  48. Jiang, S.; Cao, J.; Wu, H.; Yang, Y.; Ma, M.; He, J. BlocHIE: A BLOCkchain-Based Platform for Healthcare Information Exchange. In Proceedings of the 2018 IEEE International Conference on Smart Computing (SMARTCOMP), Sicily, Italy, 18–20 June 2018; pp. 49–56. 
  49. Ji, Y.; Zhang, J.; Ma, J.; Yang, C.; Yao, X. BMPLS: Blockchain-Based Multi-level Privacy-Preserving Location Sharing Scheme for Telecare Medical Information Systems. J. Med Syst. 2018, 42, 147. 
  50. Uddin, M.A.; Stranieri, A.; Gondal, I.; Balasubramanian, V. Continuous Patient Monitoring with a Patient Centric Agent: A Block Architecture. IEEE Access 2018, 6, 32700–32726. 
  51. Mamoshina, P.; Ojomoko, L.; Yanovich, Y.; Ostrovski, A.; Botezatu, A.; Prikhodko, P.; Izumchenko, E.; Aliper, A.; Romantsov, K.; Zhebrak, A.; et al. Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare. Oncotarget 2017, 9, 5665–5690. 
  52. Zhao, H.; Bai, P.; Peng, Y.; Xu, R. Efficient key management scheme for health blockchain. CAAI Trans. Intell. Technol. 2018, 3, 114–118. 
  53. Cunningham, J.; Ainsworth, J. Enabling Patient Control of Personal Electronic Health Records through Distributed Ledger Technology. Stud. Health Technol. Inform. 2017, 245, 45–48. 
  54. Zhang, P.; White, J.; Schmidt, D.C.; Lenz, G.; Rosenbloom, S.T. FHIRChain: Applying Blockchain to Securely and Scalably Share Clinical Data. Comput. Struct. Biotechnol. J. 2018, 16, 267–278. 
  55. Boulos, M.N.K.; Wilson, J.T.; Clauson, K.A. Geospatial blockchain: Promises, challenges, and scenarios in health and healthcare. Int. J. Health Geogr. 2018, 17, 25. 
  56. Tseng, J.-H.; Liao, Y.-C.; Chong, B.; Liao, S.-W. Governance on the Drug Supply Chain via Gcoin Blockchain. Int. J. Environ. Res. Public Health 2018, 15, 1055. 
  57. Griggs, K.N.; Ossipova, O.; Kohlios, C.P.; Baccarini, A.N.; Howson, E.A.; Hayajneh, T. Healthcare Blockchain System Using Smart Contracts for Secure Automated Remote Patient Monitoring. J. Med. Syst. 2018, 42, 130. 
  58. Yue, X.; Wang, H.; Jin, D.; Li, M.; Jiang, W. Healthcare Data Gateways: Found Healthcare Intelligence on Blockchain with Novel Privacy Risk Control. J. Med Syst. 2016, 40, 453. 
  59. Cichosz, S.L.; Stausholm, M.N.; Kronborg, T.; Vestergaard, P.; Hejlesen, O. How to Use Blockchain for Diabetes Health Care Data and Access Management: An Operational Concept. J. Sci. Technol. 2018, 13, 248–253. 
  60. Nugent, T.; Upton, D.; Cimpoesu, M. Improving data transparency in clinical trials using blockchain smart contracts. F1000 Res. 2016, 5, 2541. 
  61. Liang, X.; Zhao, J.; Shetty, S.; Liu, J.; Li, D. Integrating blockchain for data sharing and collaboration in mobile healthcare applications. In Proceedings of the 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Montreal, QC, Canada, 8–13 October 2017; pp. 1–5. 
  62. Marefat, M.; Juneja, A. Leveraging Blockchain for Retraining Deep Learnign Architecture in Patient-Specific Arrhythmia Classification. In Proceedings of the 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), Las Vegas, NV, USA, 4–7 March 2018.
  63. Zhao, H.; Zhang, Y.; Peng, Y.; Xu, R. Lightweight Backup and Efficient Recovery Scheme for Health Blockchain Keys. In Proceedings of the 2017 IEEE 13th International Symposium on Autonomous Decentralized System (ISADS), Bangkok, Thailand, 22–24 March 2017; pp. 229–234. 
  64. Fan, K.; Wang, S.; Ren, Y.; Li, H.; Yang, Y. MedBlock: Efficient and Secure Medical Data Sharing Via Blockchain. J. Med Syst. 2018, 42, 136. 
  65. Al Omar, A.; Rahman, M.S.; Basu, A.; Kiyomoto, S. MediBchain: A Blockchain Based Privacy Preserving Platform for Healthcare Data. In Human Centered Computing; Springer Nature: Basingstoke, UK, 2017; Volume 10658, pp. 534–543. 
  66. Liu, P.T.S. Medical Record System Using Blockchain, Big Data and Tokenization. In Human Centered Computing; Springer Nature: Basingstoke, UK, 2016; Volume 9977, pp. 254–261. 
  67. Azaria, A.; Ekblaw, A.; Vieira, T.; Lippman, A. MedRec: Using Blockchain for Medical Data Access and Permission Management. In Proceedings of the 2016 2nd International Conference on Open and Big Data (OBD), Vienna, Austria, 22–24 August 2016; pp. 25–30. 
  68. Xia, Q.; Sifah, E.B.; Asamoah, K.O.; Gao, J.; Du, X.; Guizani, M. MeDShare: Trust-Less Medical Data Sharing Among Cloud Service Providers via Blockchain. IEEE Access 2017, 5, 14757–14767. 
  69. Zhang, P.; Walker, M.A.; White, J.; Schmidt, D.C.; Lenz, G. Metrics for assessing blockchain-based healthcare decentralized apps. In Proceedings of the 2017 IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom), Dalian, China, 12–15 October 2017; pp. 1–4. 
  70. Zhou, L.; Wang, L.; Sun, Y. MIStore: A Blockchain-Based Medical Insurance Storage System. J. Med. Syst. 2018, 42, 149. 
  71. Mytis-Gkometh, P.; Efraimidis, P.S.; Kaldoudi, E.; Drosatos, G. Notarization of Knowledge Retrieval from Biomedical Repositories Using Blockchain Technology. In IFMBE Proceedings; Springer Nature: Basingstoke, UK, 2017; Volume 66, pp. 69–73. 
  72. Roehrs, A.; Da Costa, C.A.; Righi, R.D.R. OmniPHR: A distributed architecture model to integrate personal health records. J. Biomed. Inform. 2017, 71, 70–81. 
  73. Shae, Z.; Tsai, J.J. On the Design of a Blockchain Platform for Clinical Trial and Precision Medicine. In Proceedings of the 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), Atlanta, GA, USA, 5–8 June 2017; pp. 1972–1980. 
  74. Radanović, I.; Likić, R. Opportunities for Use of Blockchain Technology in Medicine. Appl. Health Econ. Health Policy 2018, 16, 583–590. 
  75. Firdaus, A.; Anuar, N.B.; Ab Razak, M.F.; Hashem, I.A.T.; Bachok, S.; Sangaiah, A.K. Root Exploit Detection and Features Optimization: Mobile Device and Blockchain Based Medical Data Management. J. Med. Syst. 2018, 42, 112. 
  76. Dubovitskaya, A.; Xu, Z.; Ryu, S.; Schumacher, M.; Wang, F. Secure and Trustable Electronic Medical Records Sharing Using Blockchain. AMIA. Annual Symposium proceedings. In Proceedings of the AMIA 2017 Annual Symposium, Washington, DC, USA, 4–8 November 2017; pp. 650–659. 
  77. Guo, R.; Shi, H.; Zhao, Q.; Zheng, D. Secure Attribute-Based Signature Scheme with Multiple Authorities for Blockchain in Electronic Health Records Systems. IEEE Access 2018, 6, 11676–11686. 
  78. Wang, H.; Song, Y. Secure Cloud-Based EHR System Using Attribute-Based Cryptosystem and Blockchain. J. Med. Syst. 2018, 42, 152. 
  79. Saravanan, M.; Shubha, R.; Marks, A.M.; Iyer, V. SMEAD: A secured mobile enabled assisting device for diabetics monitoring. In Proceedings of the 2017 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), Odisha, India, 17–20 December 2017; pp. 1–6. 
  80. Wong, M.C.; Yee, K.C.; Nøhr, C. Socio-Technical Considerations for the Use of Blockchain Technology in Healthcare. Stud. Health Technol. Inform. 2018, 247, 636–640. 
  81. Ichikawa, D.; Kashiyama, M.; Ueno, T. Tamper-Resistant Mobile Health Using Blockchain Technology. JMIR mHealth uHealth 2017, 5, e111. 
  82. Angeletti, F.; Chatzigiannakis, I.; Vitaletti, A. The role of blockchain and IoT in recruiting participants for digital clinical trials. In Proceedings of the 2017 25th International Conference on Software, Telecommunications and Computer Networks (SoftCOM), Split, Croatia, 21–23 September 2017; pp. 1–5. 
  83. Zhang, A.; Lin, X. Towards Secure and Privacy-Preserving Data Sharing in e-Health Systems via Consortium Blockchain. J. Med. Syst. 2018, 42, 140. 
  84. Rifi, N.; Rachkidi, E.; Agoulmine, N.; Taher, N.C. Towards using blockchain technology for eHealth data access management. In Proceedings of the 2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME), Beirut, Lebanon, 19–21 October 2017; pp. 1–4. 
  85. Shae, Z.; Tsai, J. Transform Blockchain into Distributed Parallel Computing Architecture for Precision Medicine. In Proceedings of the 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), Vienna, Austria, 2–5 July 2018. 
  86. Gatteschi, V.; Lamberti, F.; DeMartini, C.; Pranteda, C.; Santamaria, V. Blockchain and Smart Contracts for Insurance: Is the Technology Mature Enough? Future Internet 2018, 10, 20. 

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