Hadoop Map Only Job for Enciphering Patient-Generated Health Data

2019 ◽  
pp. 302-317
Author(s):  
Arushi Jain ◽  
Vishal Bhatnagar
Keyword(s):  
Health Care ◽  
Big Data ◽  
Health Sector ◽  
Big Data Analytics ◽  
Data Encryption ◽  
Medical Product ◽  
Personal Health Information ◽  
Personal Health ◽  
Nature Of Information ◽  
Computer Based

Today, Big Data is being leveraged in many industries from criminal justice to health care to real estate with powerful outcomes. Organizations are using Big Data to predict the future in turn making them smarter and efficient. All the health care data such as discharge and transfer patient data maintained in Computer based Patient Records (CPR), Personal Health Information (PHI), and Electronic Health Records (EHR). The use of Big Data analytics is becoming increasingly popular at health care centres, in clinical research, and consumer based medical product development. The biggest challenge with implementation of big data is that the nature of information of public health sector is of very sensitive nature and needs to be protected from unauthorized access and release of contents. Therefore, to provide solution to the deidentifying personal health big data in this paper we author make use of only mapper job framework for data encryption.

Hadoop Map Only Job for Enciphering Patient-Generated Health Data

2017 ◽  
Vol 7 (4) ◽  
pp. 72-86
Author(s):  
Arushi Jain ◽  
Vishal Bhatnagar
Keyword(s):  
Health Care ◽  
Big Data ◽  
Health Sector ◽  
Big Data Analytics ◽  
Data Encryption ◽  
Medical Product ◽  
Personal Health Information ◽  
Personal Health ◽  
Nature Of Information ◽  
Computer Based

Today, Big Data is being leveraged in many industries from criminal justice to health care to real estate with powerful outcomes. Organizations are using Big Data to predict the future in turn making them smarter and efficient. All the health care data such as discharge and transfer patient data maintained in Computer based Patient Records (CPR), Personal Health Information (PHI), and Electronic Health Records (EHR). The use of Big Data analytics is becoming increasingly popular at health care centres, in clinical research, and consumer based medical product development. The biggest challenge with implementation of big data is that the nature of information of public health sector is of very sensitive nature and needs to be protected from unauthorized access and release of contents. Therefore, to provide solution to the deidentifying personal health big data in this paper we author make use of only mapper job framework for data encryption.

scholarly journals De-Identified Personal Health Care System Using Hadoop

2015 ◽  
Vol 5 (6) ◽  
pp. 1492 ◽  
Author(s):  
Dasari Madhavi ◽  
B.V. Ramana
Keyword(s):  
Health Care ◽  
Big Data ◽  
Health Information ◽  
Health Care System ◽  
Demographic Data ◽  
Data File ◽  
Personal Health Information ◽  
Map Reduce ◽  
Personal Health ◽  
Care System

Hadoop technology plays a vital role in improving the quality of healthcare by delivering right information to right people at right time and reduces its cost and time. Most properly health care functions like admission, discharge, and transfer patient data maintained in Computer based Patient Records (CPR), Personal Health Information (PHI), and Electronic Health Records (EHR). The use of medical Big Data is increasingly popular in health care services and clinical research. The biggest challenges in health care centers are the huge amount of data flows into the systems daily. Crunching this Big Data and de-identifying it in a traditional data mining tools had problems. Therefore to provide solution to the de-identifying personal health information, Map Reduce application uses jar files which contain a combination of MR code and PIG queries. This application also uses advanced mechanism of using UDF (User Data File) which is used to protect the health care dataset. De-identified personal health care system is using Map Reduce, Pig Queries which are needed to be executed on the health care dataset. The application input dataset that contains the information of patients and de-identifies their personal health care.  De-identification using Hadoop is also suitable for social and demographic data.

Analysis of Big Data Analytics in Healthcare Sector: Applications and Tools

2020 ◽  
Vol 17 (12) ◽  
pp. 5605-5612
Author(s):  
A. Kaliappan ◽  
D. Chitra
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Health Sector ◽  
Big Data Analytics ◽  
High Volume ◽  
Healthcare Sector ◽  
Genome Database ◽  
Tremendous Amount ◽  
The Impact ◽  
Different Sources

In today’s world, an immense measure of information in the form of unstructured, semi-structured and unstructured is generated by different sources all over the world in a tremendous amount. Big data is the termed coined to address these enormous amounts of data. One of the major challenges in the health sector is handling a high-volume variety of data generated from diverse sources and utilizing it for the wellbeing of human. Big data analytics is one of technique designed to operate with monstrous measures of information. The impact of big data in healthcare field and utilization of Hadoop system tools for supervising the big data are deliberated in this paper. The big data analytics role and its theoretical and conceptual architecture include the gathering of diverse information’s such as electronic health records, genome database and clinical decisions support systems, text representation in health care industry is investigated in this paper.

Strategic issues of big data analytics applications for managing health-care sector: a systematic literature review and future research agenda

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rajesh Kumar Singh ◽  
Saurabh Agrawal ◽  
Abhishek Sahu ◽  
Yigit Kazancoglu
Keyword(s):  
Health Care ◽  
Big Data ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Health Care Sector ◽  
Future Research ◽  
Research Gaps ◽  
Content Type

PurposeThe proposed article is aimed at exploring the opportunities, challenges and possible outcomes of incorporating big data analytics (BDA) into health-care sector. The purpose of this study is to find the research gaps in the literature and to investigate the scope of incorporating new strategies in the health-care sector for increasing the efficiency of the system.Design/methodology/approachFora state-of-the-art literature review, a systematic literature review has been carried out to find out research gaps in the field of healthcare using big data (BD) applications. A detailed research methodology including material collection, descriptive analysis and categorization is utilized to carry out the literature review.FindingsBD analysis is rapidly being adopted in health-care sector for utilizing precious information available in terms of BD. However, it puts forth certain challenges that need to be focused upon. The article identifies and explains the challenges thoroughly.Research limitations/implicationsThe proposed study will provide useful guidance to the health-care sector professionals for managing health-care system. It will help academicians and physicians for evaluating, improving and benchmarking the health-care strategies through BDA in the health-care sector. One of the limitations of the study is that it is based on literature review and more in-depth studies may be carried out for the generalization of results.Originality/valueThere are certain effective tools available in the market today that are currently being used by both small and large businesses and corporations. One of them is BD, which may be very useful for health-care sector. A comprehensive literature review is carried out for research papers published between 1974 and 2021.

scholarly journals BIG DATA BUSINESS ANALYTICS AS A STRATEGIC ASSET FOR HEALTH CARE INDUSTRY

2019 ◽  
Vol 01 (02) ◽  
pp. 12-20 ◽  
Author(s):  
Smys S ◽  
Vijesh joe C
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Health Care Industry ◽  
Customer Relationship ◽  
Business Strategies ◽  
Business Analytics ◽  
Care Industry ◽  
Strategic Assets

The big data includes the enormous flow of data from variety of applications that does not fit into the traditional data base. They deal with the storing, managing and manipulating of the data acquired from various sources at an alarming rate to gather valuable insights from it. The big data analytics is used provide with the new and better ideas that pave way to the improvising of the business strategies with its broader, deeper insights and frictionless actions that leads to an accurate and reliable systems. The paper proposes the big data analytics for the improving the strategic assets in the health care industry by providing with the better services for the patients, gaining the satisfaction of the patients and enhancing the customer relationship.

Usage and Analysis of Big Data in E-Health Domain

2018 ◽  
pp. 230-242
Author(s):  
Sushruta Mishra ◽  
Hrudaya Kumar Tripathy ◽  
Brojo Kishore Mishra ◽  
Soumya Sahoo
Keyword(s):  
Health Care ◽  
Big Data ◽  
Health Care Financing ◽  
Big Data Analytics ◽  
Semantic Interpretation ◽  
Clinical Practices ◽  
Related Data ◽  
Early Disease Detection ◽  
Growth Area ◽  
New Drug Development

Big data analytics is a growth area with the potential to provide useful insight in healthcare. Big Data can unify all patient related data to get a 360-degree view of the patient to analyze and predict outcomes. It can improve clinical practices, new drug development and health care financing process. It offers a lot of benefits such as early disease detection, fraud detection and better healthcare quality and efficiency. This chapter introduces the Big Data concept and characteristics, health care data and some major issues of Big Data. These issues include Big Data benefits, its applications and opportunities in medical areas and health care. Methods and technology progress about Big Data are presented in this study. Big Data challenges in medical applications and health care are also discussed. While many dimensions of big data still present issues in its use and adoption, such as managing the volume, variety, velocity, veracity, and value, the accuracy, integrity, and semantic interpretation are of greater concern in clinical application.

Real Time Analysis Based on Intelligent Applications of Big Data and IoT in Smart Health Care Systems

2020 ◽  
pp. 1839-1857
Author(s):  
Mamata Rath
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Treatment Plan ◽  
Big Data Analytics ◽  
Data Sets ◽  
Care Services ◽  
Real Time Analysis ◽  
Health Care Applications ◽  
Care Systems

Currently, there is an expanding interest for additional medical data from patients about their healthcare choices and related decisions, and they further need investment in their basic health issues. Big data provides patients presumptuous data to help them settle on the best choice and align with their medicinal treatment plan. One of the very advanced concepts related to the synthesis of big data sets to reveal the hidden pattern in them is big data analytics. It involves demanding techniques to mine and extract relevant data that includes the actions of piercing a database, effectively mine the data, query and inspect the data and is committed to enhance the technical execution of various task segments. The capacity to synthesize a lot of data can enable an association to manage data that can influence the business. In this way, the primary goal of big data analytics is to help business relationships to have enhanced comprehension of data, and subsequently, settle on proficient and very much educated decisions. Big data analytics empowers data diggers and researchers to examine an extensive volume of data that may not be outfit utilizing customary apparatuses. Big data analytics require advances and statistical instruments that can change a lot of organized, unstructured, and semi-organized data into more reasonable data and metadata designed for explanatory procedures. There is tremendous positive potential concerning the application of big data in human health care services and many related major applications are still in their developmental stages. The deployment of big data in health service demonstrates enhancing health care results and controlling the expenses of common people due to treatment, as proven by some developing use cases. Keeping in view such powerful processing capacity of big data analytics in various technical fields of modern civilization related to health care, the current research article presents a comprehensive study and investigation on big data analytics and its application in multiple sectors of society with significance in health care applications.

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