P4 Submission 1 Draft 12th April

Introduction

Currently, the digitisation of health care has produced an overwhelming amount of data. Mobile apps such as Fitbit and Apple Health are some of the leading contributors. To date, the main focus of these types of solutions has been the collection of diet and exercise information, yet they have unbelievable potential to provide a big data solution that could transform the way that health information is collected and used CITATION Har17 l 7177 (Ramesh, 2017). It was reported around 165 0000 mobile health applications were available for tablets and smartphones CITATION Sat15 l 7177 (Misra, 2015).

About 60% of these treat overall well-being issues like fitness, lifestyle, and diet, with the rest focusing on specific problems in the health, medication details and reminders as well as women’s health and pregnancy CITATION Sat15 l 7177 (Misra, 2015).

Cloud computing is new technology that enables access to stored information from anywhere at any time and is suitable to enhance productivity and improve performance in various organizations and people, reducing costs and complexities CITATION Lin09 l 7177 (Qian, et al.

, 2009). Integrating mobile devices into the cloud to use the unlimited cloud service provided via the mobile device results in mobile cloud computing. Because of the wider available smartphones and tablets, the cloud’s access to big data via Mobile devices (called mobile cloud computing) significantly expands the reach of big data CITATION Bah16 l 7177 (Bahwaireth & Tawalbeh, 2016).

Mobile cloud computing (MCC) will benefit several areas, including cloud-based healthcare systems. For example, the MCC healthcare system has been designed for the collection and analysis of biomedical signals from users in different locations in real time (such as ECG and Blood Pressure) .

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A custom health app is installed on the mobile device and health data is synchronized to the cloud computing service of the healthcare for storage and analysis CITATION Fon13 l 7177 (Fong & Chung, 2013).

Doug Laney (2001) referred the “3 Vs” as Volume, Variety and Velocity of complex and huge data. Although CIOs in healthcare can benefit from all 3, the emphasis should be on variety, which is a trend not merely in healthcare but in every sector CITATION Add18 l 7177 (Addams, 2018). However, the application of Big Data and predicative analysis combined with mobile data can be a major player in healthcare delivery CITATION Chr l 7177 (Christodoulakis, et al., 2016). Imagine if a mobile app could provide a stable, real-time stream of data to its eco-system of caregivers, family members, friends, doctors and further stakeholders that an individual of the program manages. Finally, a solution that leverages Big Data would collect, analyse and rationalize the data.

Big data is a growing IT trend, including cloud computing and immensely powerful information technology CITATION May13 l 7177 (Mayer-Sch?nberger & Cukier, 2013). While big data literally means big data, its concept in business sectors like healthcare remains unclear. It is useful to explore what Big Data features have, where they can be used or why they are important.

Not only can a physician look at historical information about a patient (test results, blood functions, vitals, x-rays, surgical backgrounds), but also real-time data on stress, exercise, diet, lifestyle. The example of Big Data could even map this information to other anonymous data in order to get a sense of a general health trend of their patients, in relation to families, friends, employees or the general population. A patient providing valuable data in combination with caregivers using Big Data can significantly improve the building of strategic decision-making for healthcare CITATION Har17 l 7177 (Ramesh, 2017).

Research Background

Big Data offers the potential to supply comprehensive, only accessed and processed statistical information through innovative software. In terms of efficient management of hospital assets and records, Big Data Analytics is highly beneficial. In addition, it is used to develop mobile applications, which store all medical patient data, reducing the need for excessive paperwork again. Instead of managing databases, this allows medical experts to focus more on the care and treatment of patients CITATION Pat19 l 7177 (Patil, 2019).

The development of a variety of mobile applications for various applications in healthcare is the result of this kind of technological trend. A number of mobile applications allow people in their area to search the medical practitioners, read their reviews and other patient feedback and, if they are satisfied with the information they find, arrange an online meeting CITATION Pat19 l 7177 (Patil, 2019). They can also download, store and order medicines online at affordable prices. In addition they can do their work. Mobile applications also provide all the patient data from past medical history to performance measurements, patient feedback, changes to treatment patterns and schedules, to the smartphone application by pressing a button, for a physician to consider and decide whether to go CITATION Pat19 l 7177 (Patil, 2019). Since everything is recorded in real time, the physicians can easily change shifts without explaining the patient’s condition to the next physician in person. All data needed by monitoring or nurses are in the mobile application.

Big data is recently referred to as the enormous amount of data acquired due to the revolutionary progress in various technologies, including cloud computing, mobile health applications and wireless communication technology. It is determined by: data size (volume), data types based on productive source (variety) and time frame for data generation (velocity) CITATION Lan01 l 7177 (Laney, 2001).

The adoption of Big Data can transform the industry into value-based treatment, separating it from a fee-for-service model CITATION McD17 l 7177 (McDonald, 2017). In short, it could guarantee that medical costs will be reduced while revealing the ways that excellent patient meetings, procedures and results will be provided.

Research Problem

“Big Data in healthcare” identifies the abundance of health data collected from various sources, e.g. digital health records (EHRs), medical imaging, genomic sequenced, pharmaceutical research, wearables and medical equipment CITATION NEJ18 l 7177 (Catalyst, 2018). Three characteristics make it distinctive from the traditional data used in decision making in electronic medical and human wellness::

It really is achieved in extremely high volumes,

it travels at high velocity and spans the substantial digital world of healthcare sector

and because it comes from many resources, its structure and nature are highly variable CITATION Kat13 l 7177 (Katal, et al., 2013).

They include volume, velocity and variety CITATION Phi11 l 7177 (Russom, 2011). With their diversity of files, types and contexts, it is truly difficult to merge large health data into regular databases, making them extremely challenging and hard for market leaders to make use of their significant guarantees to transform the industry.

CITATION Sye13 l 7177 (Syed, et al., 2013) suggested that it would be difficult to process Big Data using on-site database management tools or conventional data processing applications, because it often surpasses traditional databases’ capacities. This is one of the challenges that healthcare has been facing over the years.

In spite of these challenges, a number of new improvements in technology enable big data health care to be transformed into useful, workable information CITATION Hal15 l 7177 (Halamka, 2015). Big data informs movements to value-based healthcare by using appropriate software tools and opens the door to remarkable advances even when the costs are reduced CITATION NEJ17 l 7177 (Catalyst, 2017). With the wealth of information available in health data analytics, health care providers and administrators are able to make better medical and financial decisions while continuing to offer patient care of ever greater quality.

However, the adoption of Big Data in healthcare analyses has fallen behind various industries, due to difficulties such as mobile applications, health privacy, siloed data, security and budget constraints. In addition, 80 per cent of insurance, financial, media and entertainment, manufacturing and logistics executives have “effectively,” and several of these have already declared their Big Data initiatives to be “transformational” with regard to their companies CITATION NEJ18 l 7177 (Catalyst, 2018). This study will address integrating of Big Data and mobile application in healthcare.

Research Question

Given the need for rapid change in the healthcare industry, the unique nature of mobile applications and the options offered by this brand new technology, the following question will be made:

What mobile application has been currently developed for accessing Big Data in the healthcare sector?

The following are sub-questions:

How can you use cloud technologies to access Big Data?

What are the factors that influence Big Data in mobile health applications?

What is role of Big Data on mobile cloud computing?

Research Aim

To identify a mobile application which provides access for Big Data in the healthcare industry.

Research Objectives

To investigate how adoption of cloud technologies provide access to Big Data.

To explain the factors that influence Big Data in mobile health applications

To determine the role of Big Data on mobile cloud computing.

Delineation of the research

A study of Big Data in the healthcare sector.

A study of a mobile-based solution only.

Mobile application in healthcare.

References

BIBLIOGRAPHY Addams, A., 2018. THE ROLE OF BIG DATA AND MOBILE APPS IN HEALTHCARE. [Online] Available at: 13 March 2019].

Bahwaireth, K. & Tawalbeh, L., 2016. Cooperative models in cloud and mobile cloud computing. [Online] Available at: 13 March 2019].

Catalyst, N., 2017. What Is Value-Based Healthcare?. [Online] Available at: 17 March 2019].

Catalyst, N., 2018. What Is Big Data In Healthcare?. [Online] Available at: 17 March 2019].

Christodoulakis, A., Karanikas, H., Billiris Antonis, T. E. & Pelekis, N., 2016. “Big data” in health care Assessment of the performance of Greek NHS hospitals using key performance and clinical workload indicators. [Online] Available at: 14 March 2019].

Fong, E.-M. & Chung, W.-Y., 2013. Mobile Cloud-Computing-Based Healthcare Service by Noncontact ECG Monitoring. [Online] Available at: 13 March 2019].

Halamka, J. D., 2015. Using Big Data to Make Wiser Medical Decisions. [Online] Available at: 17 March 2019].

Katal, A., Wazid, M. & Goudar, R. H., 2013. Big data: Issues, challenges, tools and Good practices. [Online] Available at: 17 March 2019].

Laney, D., 2001. 3D Management: Controlling Data Volume, Velocity, and Variety. [Online] Available at: 13 March 2019].

Mayer-Sch?nberger, V. & Cukier, K., 2013. Big Data: A Revolution That Will Transform How We Live, Work, and Think. [Online] Available at: 14 March 2019].

McDonald, C., 2017. 5 Big Data Trends in Healthcare for 2017. [Online] Available at: 17 March 2019].

Misra, S., 2015. IMS Health Apps Report. [Online] Available at: 13 March 2019].

Patil, R., 2019. How are Mobile apps transforming the healthcare industry?. [Online] Available at: 14 March 2019].

Qian, L., Luo, Z., Du, Y. & Guo, L., 2009. Cloud Computing: An Overview. [Online] Available at: 13 March 2019].

Ramesh, H., 2017. Big Data Makes Mobile Health Care Apps Healthier. [Online] Available at: 13 March 2019].

Russom, P., 2011. TDWI best practices report Big Data Analytics. [Online] Available at: 19 March 2019].

Syed, A. R., Gillela, K. & Venugopal, C., 2013. The Future Revolution on Big Data. International Journal of Advanced Research in Computer and Communication Engineering, 2(6), pp. 2446-2451.