Big Data Personal Health Records Management and Analysis on Cloud Using No SQL-Mongo DB

International Journal of Computer Trends and Technology (IJCTT)          
© 2015 by IJCTT Journal
Volume-28 Number-2
Year of Publication : 2015
Authors : Sophia Kingsley Okore, Edwin Sweety Bakyarani


Sophia Kingsley Okore, Edwin Sweety Bakyarani "Big Data Personal Health Records Management and Analysis on Cloud Using No SQL-Mongo DB". International Journal of Computer Trends and Technology (IJCTT) V28(2):68-74, October 2015. ISSN:2231-2803. Published by Seventh Sense Research Group.

Abstract -
The advent of digital technology over the years has led to data explosion “Big Data” which requires huge storage facilities and advanced processing, accessing, analyzing, visualizing techniques. The emergence of cloud computing allows vast computations to run inexpensively and efficiently. Big data systems like Hadoop are designed to run on commodity hardware and can process huge data of any data types, which makes operational data workloads much easier to manage, cheaper to implement. The concept of Big Data, cloud computing and No SQL-Mongo DB database technologies can support a new generation of cloud-based Personal Health Records (PHR) services that contain heterogeneous (unstructured, semi-structured and structured) patient data (health, social and lifestyle). In this project the concept of Big Data and the effective way to handle data using the PHR as a case study as well as the EHR is analyzed. My focus is on using Mongo DB: a No SQL database for storage and processing over the traditional RDBMS. In the proposed system, Personal Health Record (PHR) is an emerging patient-centric in Cloud Computing Servers. User Files are automatically placed in the Public & Private Cloud (i.e. Mongo DB) based on the Sensitiveness of the Data. Normal Files are placed in the Public Cloud, Secured Data in Private Cloud. Multiple MongoDB Cloud is deployed for fast Data Retrieval.

[1] Wasan, Siri Krishan, Vasudha Bhatnagar, and Harleen Kaur. "The impact of data mining techniques on medical diagnostics." Data Science Journal 5.19 (2006): 119-124.
[2] J. S. Kahn, V. Aulakh and A. Bosworth, "What It Takes: Characteristics Of The Ideal Personal Health Record", Health Affairs, 28 (2009), pp. 369-376.
[3] J. D. Halamka, K. D. Mandl and P. C. Tang, "Early Experiences with Personal Health Records", Journal of the American Medical Informatics Association, 15 (2008), pp. 1-7.
[4] B. Tulu and T. A. Horan, "The electronic disability record: purpose, parameters, and model use case", Journal of the American Medical Informatics Association : JAMIA, 16 (2009), pp. 7-13.
[5] T. Undem, Consumers and Health Information Technology: A National Survey, California HealthCare Foundation, Oakland, CA, 2010.
[6] L. Sprague, "Personal health records: the people's choice?", NHPF issue brief / National Health Policy Forum, George Washington University (2006), pp. 1-13
[7] D. B. Lafky and T. A. Horan, "Personal health records", Health Informatics Journal, 17 (2011), pp. 63-71.
[8] Information security risk measures for Cloud-based Personal Health Records Avuya Mxoli1+2, Mariana Gerber1 and Nicky Mostert-Phipps1, International Conference on Information Society (i-Society 2014) .
[9] Galen Gruman: of-things-what-it-is-where-its-going retrieved on 24/09/15
[10] Yao Zheng: Privacy-Preserving Personal Health Record System Using Attribute-Based Encryption, A Thesis Submitted to the Faculty of the WORCESTER POLYTECHNIC INSTITUTE In partial ful_llment of the requirements for the Degree of Master of Science In Electrical & Computer Engineering by June 2011
[11] Rajaraman, Anand, and Jeffrey David Ullman. Mining of massive datasets. Cambridge University Press, 2012
[12] Groves, Peter, et al. "The „big data revolution in healthcare." McKinsey Quarterly (2013)
[13], Retrieved May 2014.
[14] Manyika, James, et al. "Big data: The next frontier for innovation, competition, and productivity." (2011).
[15] IBM Industry supporting Healthcare Information Retrieved 2014 from ttp:// html IJCATM
[16] Gartner. Big Data Definition. 2013 [cited 2013 10/04/2013]; Available from: [17] L, H., et al., Securing the e-health cloud, in Proceedings of the 1st ACM International Health InformaticsSymposium2010, ACM: Arlington, Virginia, USA. p. 220-229.
[18] Wei, Z., et al. A tuple-oriented bucket partition index with minimum weighted mean of interferential numbers for DAS models. in Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on. 2010.
[19] Chimeze Ogbuji, Karthik Gomadam, Charles Petrie.: Web Technology and Architecture for Personal Health Records. ARTICLE in IEEE Internet Computing · July 2011.
[20] Jagdev Bhogal; Imran Choksi : Handling Big Data using NoSQL, 2015 29th International Conference on Advanced Information Networking and Applications Workshops

Big data, cloud computing, PHR, No SQL-Mongo DB.