ITECH 5500 The Role of Big Data in Health Care Assessment Answer
PROFESSIONAL RESEARCH AND COMMUNICATION
A. Interim research proposal:
The role of big data in health care
Big data have changed the way of data management and data analysis in different industries. One of the most critical areas where big data can be applied to making this change is the healthcare sector. In previous times, collection and the analysis of the vast amount of data were time-consuming and very costly. However, in the present scenario, big data has made it easier to collect these types of information and analyse it so that critical insights can be achieved from these data. Big data is generally created from the digitalisation of everything which examined by some specific technologies.
Implementation of big data not only improves the results of the bottom line or increases profitability in businesses but it also healthcare sector to predict the epidemics and improve the life and living quality (Rumsfeld, Joynt & Maddox, 2016). The average lifespan of a human is continually developing along with the population of the entire world that creates new types of challenges in the present delivery method of the treatments. For these purposes, the collection of data about the illness is necessary so that it can be used to treat the new types of disease in modern times (Wang et al. 2018). Healthcare professionals collect massive information about the patients for identifying the best strategies. This proposal sheds lights on the importance of big data in healthcare.
B. Synthesis matrix:
|Idea A||Idea B||Idea C|
|Article #1||This article provides a better overview of big data analytics. Big data is extensive, complex and challenging in the analysis (Sonnati, 2017). It is also challenging to capture the outcomes. This big data are generally created by the facilitation of the operation of an industry (Sonnati, 2017). Therefore, for identifying the outcome, it is always essential in analysing that information. For analysing big data, three different analytics are used that are predictive, descriptive and prescriptive.||The second concept is related to big data in the health sector. Hadoop data processing has become one of the computational strategies that increase the quality of the output. Big data is essential in discovering a new technique for analysing data and increasing accuracy in the results (Sonnati, 2017). Hadoop data processing framework is not only useful in increasing efficiencies in the treatment process, but it is also helpful in quality in the process of care.||The third concepts that are provided in the article are related to the data lifecycle. According to the data lifecycle, there are five phases to process big data to use it in the healthcare sector (Sonnati, 2017). The first phase is the collection of data where data are collected from different sources. The second phase is involved in pre-processing the data where data are stored in the common storage (Sonnati, 2017). After that, information is reduced and transformed by applying different algorithms. Then, data analytics play an essential role in analysing data for concluding (Sonnati, 2017). After that, data is represented in the recognisable form of a human.|
|Article #2||The first concept offers usefulness along with challenges of big data in health (Fatt & Ramadas, 2018). Big data is highly useful in predicting the disease-related outcome, preventing premature deaths and improving the process of treatments. Data about the issues in treatments and different types of disease are provided by the big data (Fatt & Ramadas, 2018). This not only helps the healthcare professional in developing a treatment to increase mortality, but it is also helpful for the government in saving costs for the healthcare sector (Fatt & Ramadas, 2018). Therefore, big data assists the government as well as the non-government company in formulating different strategies, policies and procedures about the standard of treatment or the development of drugs.||The second concept that is provided by the article is the benefits of the big data. According to the idea, in healthcare, big data is approapriate for facilitating predictive analysis that helps in identifying medical issues before its occurrence (Fatt & Ramadas, 2018). Therefore, by using big data, professional of the healthcare can reduce health risks among the patients. Big data is also useful in facilitating electronic keeping record, managing data and analysing data. Big data helps enable clinical trials (Fatt & Ramadas, 2018). It is also helpful in offering a clearer picture of the population types and the medical problem associated with them.||The third concept provides useful concepts about the issues associated with big data (Fatt & Ramadas, 2018). Though big data helps manage data in healthcare and advance the treatment process, it has considerable challenges in protecting data that are collected from the healthcare sector (Fatt & Ramadas, 2018). Data classification is the issues associated with big data (Fatt & Ramadas, 2018). This is because; big data is less structured, massive and heterogeneous. It is difficult in classifying and identifying data flor its effective utilisation. Security is one of the significant issues in using big data (Fatt & Ramadas, 2018). Therefore, it is essential to protect the health information with the help of multilayer authentication and a good antivirus.|
|Article #3||The first concepts that are offered by this particular article are the big data’s definition. This article explained that big data is large volume, complex as well as variable information that requires advancements in the technology for enabling, distributing, capturing along with analysing information. Therefore, in the healthcare sector, big data collects large quantities of data from various organisations that are belonging to the healthcare (Senthilkumar et al. 2018). This is because it helps make an active decision by managing, analysing, delivering and visualising data.||The second concepts that are offered by the article are related to the process of analysis of big data (Senthilkumar et al. 2018). For processing this type of data, the analytics follows different processes, which are data acquisition, storage of information, management and analysis of the information along with the visualisation of the information (Senthilkumar et al. 2018). For acquisition of data in the healthcare sector, mainly electronic health records, social media, image processing and a set of the webpage that offer healthcare information are considered (Senthilkumar et al. 2018). For storing information, cloud computing is generally used. For the management of big data, organisation, clean, retrieval, data mining along with the process of data governance are typically followed. Mainly three different types of data analytics are there, such as predictive, diagnostic along with the prescriptive data analytics with the help of which data analysis are done. After the analysis of the information, big data analytics present the healthcare information into the pictorial and the graphical formats (Senthilkumar et al. 2018). This is because it develops a better understanding of the complex data so that proper decision making can be done.||The third concept that has been represented in the article is the big data’s application in health (Senthilkumar et al. 2018). Big data is applied in the omics, which helps realise the strategies about the diseases and developing better specifications about the treatments in the healthcare sector (Senthilkumar et al. 2018). Big data is also helpful in studying genomics, metabolomics and proteomics. Big data is useful in detecting frauds and managing the claim in the healthcare-based insurance organisation. Big data is applicable in the anatomical configuration and interaction of issues which helps design and manufacture medical device (Senthilkumar et al. 2018). For facilitating the discovery of drugs or the development of various pharmaceutical things, big data is highly useful. For creating personalised patient care, big data is applicable.|