The promising future of healthcare services: When big data analytics meets wearable technology

2016 ◽  
Vol 53 (8) ◽  
pp. 1020-1033 ◽  
Author(s):  
Jing Wu ◽  
He Li ◽  
Sherri Cheng ◽  
Zhangxi Lin
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Wearable Technology

Big Data and Big Data Analytics for Improved Healthcare Service and Management

2020 ◽  
Vol 8 (1) ◽  
pp. 13-51
Author(s):  
Pijush Kanti Dutta Pramanik ◽  
Saurabh Pal ◽  
Moutan Mukhopadhyay
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Healthcare Sector ◽  
Future Market ◽  
Data Generation ◽  
Related Data ◽  
Healthcare Data ◽  
Different Types

Like other fields, the healthcare sector has also been greatly impacted by big data. A huge volume of healthcare data and other related data are being continually generated from diverse sources. Tapping and analysing these data, suitably, would open up new avenues and opportunities for healthcare services. In view of that, this paper aims to present a systematic overview of big data and big data analytics, applicable to modern-day healthcare. Acknowledging the massive upsurge in healthcare data generation, various ‘V's, specific to healthcare big data, are identified. Different types of data analytics, applicable to healthcare, are discussed. Along with presenting the technological backbone of healthcare big data and analytics, the advantages and challenges of healthcare big data are meticulously explained. A brief report on the present and future market of healthcare big data and analytics is also presented. Besides, several applications and use cases are discussed with sufficient details.

Insight Into Big Data Analytics

2018 ◽  
pp. 67-79
Author(s):  
Mohd Vasim Ahamad ◽  
Misbahul Haque ◽  
Mohd Imran
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Huge Amount ◽  
Business Decision ◽  
Digital Era ◽  
Data Formats ◽  
Recent Trends ◽  
Analytical Approaches

In the present digital era, more data are generated and collected than ever before. But, this huge amount of data is of no use until it is converted into some useful information. This huge amount of data, coming from a number of sources in various data formats and having more complexity, is called big data. To convert the big data into meaningful information, the authors use different analytical approaches. Information extracted, after applying big data analytics methods over big data, can be used in business decision making, fraud detection, healthcare services, education sector, machine learning, extreme personalization, etc. This chapter presents the basics of big data and big data analytics. Big data analysts face many challenges in storing, managing, and analyzing big data. This chapter provides details of challenges in all mentioned dimensions. Furthermore, recent trends of big data analytics and future directions for big data researchers are also described.

scholarly journals Proposed Usage of ICT and Big Data in Healthcare of Madhya Pradesh

2021 ◽  
Vol 9 (12) ◽  
pp. 2242-2248
Author(s):  
Mimoh Ojha
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Madhya Pradesh ◽  
Information And Communications Technology ◽  
Area Network ◽  
Wide Area Network ◽  
Healthcare Data ◽  
Health Application

Abstract: This paper gives an insight of how information and communications technology (ICT) in combination with big data analytics can help to improve healthcare services in Madhya Pradesh, which is a state in India having approximately 75 million populations. With ongoing projects like ‘Digital India’ which will allow computerization of hospitals and digitization of healthcare data. Digital India coupled with ICT, can play an indispensable role in providing effective healthcare services through e-health application like electronic health record, e-prescription, computerized physician order entry, telemedicine, mhealth along with the network like State wide area network (SWAN) and National health information network which will allow sharing of healthcare records across the network. Data stored through e-health application is of huge size having different formats which makes it difficult to perform analytics on it. But with big data analytics we can perform analytics on large voluminous healthcare data and useful result obtained from data analytics, patients can be given better and specific treatments. It will also help doctors to exchange their knowledge and treatment practices. This paper also illustrates a case study on M.Y. hospital located in Indore, Madhya Pradesh. Keywords: ICT, E-health, Digital India, SWAN, CUG, Big Data Analytics.

scholarly journals BIG DATA ANALYTICS IN HEALTHCARE SERVICES

2019 ◽  
Vol 1 (2) ◽  
pp. 22-24
Author(s):  
GUNASEKAR THANGARASU ◽  
KAYALVIZHI SUBRAMANIAN
Keyword(s):  
Big Data ◽  
Medical Research ◽  
Patient Care ◽  
Clinical Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Effective Practices ◽  
Novel Approach

This study addresses the healthcare services problems which focus on the upcoming and promising areas of medical research and proposed a novel approach integrating in big data analytics and Apache. The proposed approach will improve the healthcare services fastly and efficiently. The big data analytics can continually evaluate clinical data in order to improve the effective practices of physicians and improved patient care

scholarly journals Quality Healthcare Prediction using K-Means And Clara Partition Based Clustering Algorithm for Big Data Analytics

2020 ◽  
Vol 9 (3) ◽  
pp. 1140-1144
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Clustering Algorithm ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Natural World ◽  
Mixed Data ◽  
Significant Information ◽  
Clustering Techniques ◽  
Vast Amount

Big Data is a collection of large or vast amount of information that grows at ever increasing rates. Big data is ordered, unstructured, semi structured or mixed data in natural world. Researchers are designing, implementing, analyzing different application. In medicinal industry large or vast amount of data is available but people are not able to extract the significant information. Healthcare big data analytics (HBDA) becomes “Healthier analytics” by fusion of techniques. In this paper, we discuss and implement algorithms of clustering using R-Studio tool. Clustering is defined as the method of partitioning set of patterns into similar groups called as clusters. We can extract the data from vast datasets in the form of clustering rules. These clustering techniques are scalable. Also, we compare the accuracies of two partition based clustering techniques k-means and Clara on healthcare datasets for giving good quality of healthcare services. Implemented results demonstrate the k-means method gives better accuracy values than Clara algorithm.

Leveraging Big Data Analytics and Hadoop in Developing India's Healthcare Services

2021 ◽  
pp. 396-407
Author(s):  
Koppula Srinivas Rao ◽  
Saravanan S. ◽  
Pattem Sampath Kumar ◽  
Rajesh V. ◽  
K. Raghu
Keyword(s):  
Developing Countries ◽  
Big Data ◽  
Medical Research ◽  
Economically Disadvantaged ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Large Populations ◽  
Disadvantaged People

The benefits of data analytics and Hadoop in application areas where vast volumes of data move in and out are examined and exposed in this report. Developing countries with large populations, such as India, face several challenges in the field of healthcare, including rising costs, addressing the needs of economically disadvantaged people, gaining access to hospitals, and conducting medical research, especially during epidemics. This chapter discusses the role of big data analytics and Hadoop, as well as their effect on providing healthcare services to all at the lowest possible cost.

An Adoption model for a big data analytics system for improving healthcare services in Burundi’s public hospitals

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Yves Habimana ◽  
Irene Moseti-Morara ◽  
Damaris Odero
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Health Care Services ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Public Hospitals ◽  
Assessment Tools ◽  
Care Services ◽  
Adoption Model

One of the key responsibilities of a government is to provide efficient health care services that are better and affordable. In Burundi, patients’ health records are collected using handwritten forms and stored in filing cabinets. Evidence’ based research and practice shows that adoption of a Big Data Analytics (BDA) system can significantly improve health care services. Unfortunately, BDA adoption models and automated assessment tools are lacking not to mention the dearth caused by researchers’ predominant focus on the technical aspects. Therefore, the aim of this study was to propose a BDA system adoption model for improving health care services in Burundi’s public hospitals. This was achieved through a mixed research method a large part being qualitative. The factors that influence the adoption of BDA in public healthcare services using the Technology Organization Environment (TOE) adoption theory through a desk research. Semi-structured interviews, observations and document reviews were used to investigate the methods used to collect, store and analyze data in Public hospitals of Burundi. Afterwards, a web based automated Adoption Readiness Assessment Tool (ARAT) was developed then used to assess the readiness of Burundi in adopting a BDA system in its public hospitals. The assessment results showed that the country has adequate telecommunication infrastructures and has started using information systems like OpenClinic and District Health Information Software 2 (DHIS2) in some public hospitals, the government has set up policies for e-Health and the level of awareness is high as well among health workers. But there are improvements to be made in order to assure that the adoption is successful. Lastly, a tailored adoption model was proposed describing what should be done and how in order to assure a successful adoption of a BDA in public hospitals.  

scholarly journals Big Data Analytics for Improved Care Delivery in the Healthcare Industry

2019 ◽  
Vol 15 (10) ◽  
pp. 40
Author(s):  
Gunasekar Thangarasu ◽  
Kayalvizhi Subramanian
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Care Delivery ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Healthcare Systems ◽  
Big Data Analysis ◽  
Unstructured Data ◽  
Effective Practices ◽  
Healthcare Industry

<p class="0abstract">The big data analytics plays a pivotal role in the field of healthcare services and research to facilitate better service to the patients. It has provided tools to accumulate, manage, analysis the structured and unstructured data produced by the healthcare systems. Recently the utilization of big data analytics has been increased in the healthcare industry for assisting the process of diagnosing diseases and care delivery. However, the adoption and research development of big data analysis in the healthcare industry is still slow down due to facing some fundamental problems inherent within the big data paradigm. In this study, addresses these problems which focus on the upcoming and promising areas of medical research and proposed a novel big data analytics approach using Apache Spark. The proposed approach will improve care delivery in the healthcare industry. Big data analytics can continually evaluate clinical data in order to improve the effective practices of physicians and improved patient care.</p>

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