Md Ashraf Uddin
ABSTRACT
Recently, a wide range of digital health record repositories has emerged. These include Electronic Health record managed by the government, Electronic Medical Record (EMR) managed by healthcare providers, Personal Health Record (PHR) managed directly by the patient and new Blockchain-based systems mainly managed by technologies. Health record repositories differ from one another on the level of security, privacy, and quality of services (QoS) they provide. Health data stored in these repositories also varies from patient to patient in sensitivity, and significance depending on medical, personal preference, and other factors. Decisions regarding which digital record repository is most appropriate for the storage of each data item at every point in time are complex and nuanced. The challenges are exacerbated with health data continuously streamed from wearable sensors. In this paper, we propose a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The model maps health data to be stored in the repositories. The mapping between health data features and characteristics of each repository is learned using a machine learning-based classifier mediated through clinical rules. Evaluation results demonstrate the model’s feasibility.
- Assad Abbas and Samee U Khan. 2015. e-Health cloud: privacy concerns and mitigation strategies. In Medical Data Privacy Handbook. Springer, 389–421.Google Scholar
- Azzah Al Ghamdi and Thomas Thomson. 2018. The Future of Data Storage: A Case Study with the Saudi Company. Journal of Electrical and Electronic Engineering 6, 1(2018), 1.Google ScholarCross Ref
- AS Albahri, AA Zaidan, OS Albahri, BB Zaidan, and MA Alsalem. 2018. Real-time fault-tolerant mHealth system: Comprehensive review of healthcare services, opens issues, challenges and methodological aspects. Journal of medical systems 42, 8 (2018), 137.Google ScholarDigital Library
- Suvini P Amaraweera and Malka N Halgamuge. 2019. Internet of Things in the Healthcare Sector: Overview of Security and Privacy Issues. In Security, Privacy and Trust in the IoT Environment. Springer, 153–179.Google Scholar
- Nureni Ayofe Azeez and Charles Van der Vyver. 2018. Security and privacy issues in e-health cloud-based system: A comprehensive content analysis. Egyptian Informatics Journal(2018).Google Scholar
- Maxim Chernyshev, Sherali Zeadally, and Zubair Baig. 2019. Healthcare Data Breaches: Implications for Digital Forensic Readiness. Journal of medical systems 43, 1 (2019), 7.Google ScholarDigital Library
- Konstantinos Christidis and Michael Devetsikiotis. 2016. Blockchains and smart contracts for the internet of things. Ieee Access 4(2016), 2292–2303.Google ScholarCross Ref
- Luca Faramondi, Gabriele Oliva, Roberto Setola, and Luca Vollero. 2019. IIoT in the Hospital Scenario: Hospital 4.0, Blockchain and Robust Data Management. In Security and Privacy Trends in the Industrial Internet of Things. Springer, 271–285.Google Scholar
- Gopi Krishna Garge, Chitra Balakrishna, and Soumya Kanti Datta. 2017. Consumer health care: Current trends in consumer health monitoring. IEEE Consumer Electronics Magazine 7, 1 (2017), 38–46.Google ScholarCross Ref
- Rui Guo, Huixian Shi, Qinglan Zhao, and Dong Zheng. 2018. Secure attribute-based signature scheme with multiple authorities for blockchain in electronic health records systems. IEEE Access 6(2018), 11676–11686.Google ScholarCross Ref
- Lei Hang, Eunchang Choi, and Do-Hyeun Kim. 2019. A Novel EMR Integrity Management Based on a Medical Blockchain Platform in Hospital. Electronics 8, 4 (2019), 467.Google ScholarCross Ref
- Lisa Hanna, Stephen D Gill, Laura Newstead, Melanie Hawkins, and Richard H Osborne. 2017. Patient perspectives on a personally controlled electronic health record used in regional Australia: ‘I can be like my own doctor’. Health Information Management Journal 46, 1 (2017), 42–48.Google ScholarCross Ref
- David P Hansen, Marcel E Dinger, Oliver Hofmann, Natalie Thorne, and Tiffany F Boughtwood. 2019. Preparing Australia for genomic medicine: data, computing and digital health. The Medical journal of Australia 210 (2019), S30–S32.Google ScholarCross Ref
- David Isern and Antonio Moreno. 2016. A systematic literature review of agents applied in healthcare. Journal of medical systems 40, 2 (2016), 43.Google ScholarDigital Library
- Gajendra J Katuwal, Sandip Pandey, Mark Hennessey, and Bishal Lamichhane. 2018. Applications of Blockchain in Healthcare: Current Landscape & Challenges. arXiv preprint arXiv:1812.02776(2018).Google Scholar
- Steven Y Ko, Kyungho Jeon, and Ramsés Morales. 2011. The HybrEx Model for Confidentiality and Privacy in Cloud Computing.HotCloud 11(2011), 8–8.Google Scholar
- Tsung-Ting Kuo, Hyeon-Eui Kim, and Lucila Ohno-Machado. 2017. Blockchain distributed ledger technologies for biomedical and health care applications. Journal of the American Medical Informatics Association 24, 6(2017), 1211–1220.Google ScholarCross Ref
- Tao Ma, Pradhumna Lal Shrestha, Michael Hempel, Dongming Peng, Hamid Sharif, and Hsiao-Hwa Chen. 2012. Assurance of energy efficiency and data security for ECG transmission in BASNs. IEEE Transactions on Biomedical Engineering 59, 4 (2012), 1041–1048.Google ScholarCross Ref
- Joshua C Mandel, David A Kreda, Kenneth D Mandl, Isaac S Kohane, and Rachel B Ramoni. 2016. SMART on FHIR: a standards-based, interoperable apps platform for electronic health records. Journal of the American Medical Informatics Association 23, 5(2016), 899–908.Google ScholarCross Ref
- Chrissa McFarlane, Michael Beer, Jesse Brown, and Nelson Prendergast. 2017. Patientory: A Healthcare Peer-to-Peer EMR Storage Network v1.Entrust Inc.: Addison, TX, USA(2017).Google Scholar
- Thomas McGhin, Kim-Kwang Raymond Choo, Charles Zhechao Liu, and Debiao He. 2019. Blockchain in healthcare applications: Research challenges and opportunities. Journal of Network and Computer Applications (2019).Google Scholar
- Md Mehedi Hassan Onik, Satyabrata Aich, Jinhong Yang, Chul-Soo Kim, and Hee-Cheol Kim. 2019. Blockchain in Healthcare: Challenges and Solutions. In Big Data Analytics for Intelligent Healthcare Management. Elsevier, 197–226.Google Scholar
- Louis Papageorgiou, Picasi Eleni, Sofia Raftopoulou, Meropi Mantaiou, Vasileios Megalooikonomou, and Dimitrios Vlachakis. 2018. Genomic big data hitting the storage bottleneck. EMBnet. journal 24(2018).Google Scholar
- B Thirumala Rao 2016. A study on data storage security issues in cloud computing. Procedia Computer Science 92 (2016), 128–135.Google ScholarCross Ref
- Arkaitz Ruiz-Alvarez and Marty Humphrey. 2012. A model and decision procedure for data storage in cloud computing. In Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012). IEEE Computer Society, 572–579.Google ScholarDigital Library
- Arkaitz Ruiz-Alvarez and Marty Humphrey. 2014. Toward optimal resource provisioning for cloud MapReduce and hybrid cloud applications. In Proceedings of the 2014 IEEE/ACM International Symposium on Big Data Computing. IEEE Computer Society, 74–82.Google ScholarDigital Library
- Jaydip Sen. 2014. Security and privacy issues in cloud computing. In Architectures and protocols for secure information technology infrastructures. IGI Global, 1–45.Google Scholar
- Ton Spil and Richard Klein. 2015. The personal health future. Health policy and technology 4, 2 (2015), 131–136.Google Scholar
- Md Ashraf Uddin, Andrew Stranieri, Iqbal Gondal, and Balasubramanian. 2018. A Patient Agent to Manage Blockchains for Remote Patient Monitoring. Studies in health technology and informatics 254 (2018), 105–115.Google Scholar
- Md Ashraf Uddin, Andrew Stranieri, Iqbal Gondal, and Venki Balasubramanian. 2018. Continuous patient monitoring with a patient centric agent: a block architecture. IEEE Access 6(2018), 32700–32726.Google ScholarCross Ref
- Vijay Vaidehi, M Vardhini, H Yogeshwaran, G Inbasagar, R Bhargavi, and C Sweetlin Hemalatha. 2013. Agent based health monitoring of elderly people in indoor environments using wireless sensor networks. Procedia Computer Science 19 (2013), 64–71.Google ScholarCross Ref
- Shangping Wang, Yinglong Zhang, and Yaling Zhang. 2018. A blockchain-based framework for data sharing with fine-grained access control in decentralized storage systems. IEEE Access 6(2018), 38437–38450.Google ScholarCross Ref
- Sobia Yaqoob, Muhammad Murad Khan, Ramzan Talib, Arslan Dawood Butt, Sohaib Saleem, Fatima Arif, and Amna Nadeem. 2019. Use of Blockchain in Healthcare: A Systematic Literature Review. International Journal of Advanced Computer Science and Applications 10, 5(2019).Google ScholarCross Ref
- Hongli Zhang, Lin Ye, Xiaojiang Du, and Mohsen Guizani. 2013. Protecting private cloud located within public cloud. In Global Communications Conference (GLOBECOM), 2013 IEEE. IEEE, 677–681.Google Scholar
- Yin Zhang, Meikang Qiu, Chun-Wei Tsai, Mohammad Mehedi Hassan, and Atif Alamri. 2015. Health-CPS: Healthcare cyber-physical system assisted by cloud and big data. IEEE Systems Journal 11, 1 (2015), 88–95.Google ScholarCross Ref
- Dynamically Recommending Repositories for Health Data: a Machine Learning Model
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