Big data in healthcare is very much essential in predicting the outcome of the disease. It helps in improving the treatment, preventing premature death and development of diseases. Big data also helps in providing information with respect to diseases along with a warning sign for treatment. It will not only prevent the hospital from any kind of mortality but helps the government bodies in saving the cost involved for medical treatment. It is considered to be advantageous for both diagnosis of clinical medicine but also helps in epidemiological research as big data will move huge amount of given data
Various bodies like government and non-government bodies can make use of data for formulation of policies and strategies. With the passage of the time, there has been an increasing demand by patient with respect to healthcare option or choices. There has been increasing demand for participation for decision making in health-care. Big data in healthcare will help the patient by providing them with up-to-date information[3]. It is mainly required for assisting them with best decision which can comply for proper medical treatment.
The upcoming pages of following essay, an overview has been given regarding the need of Big Data technology in healthcare. The last section various advantages and drawbacks of big data in healthcare will be discussed in brief.
Discussion
There are many sources where big data technology is generated. Sources of social media like Facebook, Twitter and Instagram can easily generate huge amount of data on daily basis[4]. Machine like desktop, laptop and last computer can easily generate huge amount of data. IOT stands for internet of things are nothing but various kind of device which is needed for generation of huge amount of data. Different sectors are also benefitted from big data analytics like financial service industry[5]. By combining big data with analytics can easily lead to any organization for understanding the main cause of collapse. Along with this, it helps in analyzing problems and deficiency in real time.
ICT stands for information and Communication Technology plays a key role in improving the healthcare for various individual and communities[1]. It is very much important in improving the efficiency of the health system and prevention various medical errors. By the advent of new and efficient mechanism, ICT will help the students in serving the society in much better way. eHealth can be stated as ICT powered healthcare.
One of the main characteristics of healthcare sector is that it comes up with data richness. With the help of proper diagnosis and treatment, health care has evolved a lot in last few years[2]. There is large number of sources in the given sector from which data can be generated. This particular data is known as Big Data.
Big Data can be stated as large amount of data when it claims to meet certain number of criteria like variety, volume and velocity. Big data means that there is large number of data which can be terabyte or even petabyte. It is considered to be one of the biggest challenges of big data. It requires certain amount of storage and support which is considered to be complex in nature. It is required for proper kind of distribution in various kind of source[1]. While a large number of organizations have already come up with capacity to easily store up large volume of day. The overall challenge is all about storing large volume of data. The overall challenge is all about locating, identifying and checking the various sets of data that is data set.
Big Data can be stated as the addition of different kind of data which can be both structured as well as unstructured[2]. It is mainly inclusive of social media, multimedia and various kind of financial transactions. Various kind of technology like GPS and RFID tracking of information which can be done by audio or video means can be done with the help of web content. Some of the traditional warehouses is totally based on a certain number of periods which can be done monthly and weekly basis.
Big data can be easily analyzed and processed in real time and in non-real time. It is considered to be vital for healthcare zones like clinical decision support where updates can be provided on clinical support[3]. It is a zone where access can be done on up to date basis.
It aims to provide some of vital information which can be considered to be correct for decision making and elimination of various kind of error. The present data needs to be supported by the help of automated decision making. Without any kind of present data, various kind of automated decision cannot be easily trusted[4]. It aims in forcing expensive and time-consuming along with manual review for each and every decision.
Opportunities for Big Data in healthcare
Big data comes up with large number of implications for large number of patients, researcher and lastly healthcare continents. It will ultimately create an impact on the fact that how the various players can engage themselves in the given ecosystem of healthcare. It is mainly used at the time of external data and social networking which are involved in it.
Healthcare model is all about understanding the inversion in the given old model which helps in facilities in another kind of health providers. It is kept in certain region where patient can be treated can be done in much easy way[5]. It ultimately helps in translating proper kind of revenues. This particular model is mainly required for incenting and providing compensation which is needed for providing proper kind of healthcare. Patient is considered to be a vital element which aims in reducing the overall cost along with improving the outcomes. Patients need to be provided with proper kind of information and they should be guided[6]. In most of the scenario, it is seen that proper data is required for guidance which ultimately helps in decision making. This whole thing will ultimately be led to better kind of programs for treatment.
Apart from various kind of data which is required for demographics and medical history. There are some other kinds of data source where all the information of patient is provided about themselves[7]. When the whole thing is combined with outcomes, then high quality of data can be easily provided. It can easily become a source of information for various kind of researchers. It is very much helpful in reducing the overall cost and providing a boost of outcomes along with improving treatment.
Accuracy: Various people around the globe can easily understand and have an idea regarding their weight. It aims to engaging some of the negative kind of behavior for people which is all about smoking[8]. They tend to focus on some of positive behavior that is exercise. This issues inaccuracy can be easily used for dealing with the help of big data processing which aims to improve the accuracy time.
Concern for privacy: In most of the cases, it is seen that people are associated neglect to provide information about that particular individual. It is mainly done because of privacy issues and another type of related concern[9]. Certain number of creative methods can be done for encouraging and adversely affecting the business quality. Proper kind of mechanism should come into picture which is required for ensuring the privacy of given data. Proper kind of effective mechanism should be put into action which is required for assuring put the whole picture into action.
Consistency: Certain number of standard needs to be maintained which is needed for implementing the self-report data for various kind of healthcare system. It is mainly required for increasing the usefulness of overall data.
Facilities: There is certain number of facilities which is based on e-health and m-health which highlights two major parts that is mobility and social networking. It requires to be creatively employee for some data which can easily improve the level of self-reporting which is developed by certain number of communities.
Social media will ultimately improve the various kind of challenges between patient, communities and lastly providers. It will not only work for globalization and effecting healthcare. It will not only work to globalize but can be also considered to be an important source for big data. Data from social networking comes up with huge number of challenges like volume, improper structure and lastly velocity. It emphasizes certain number of challenges which aims to build up around accuracy and proper integration.
Big Data Challenges
In healthcare, there is no kind of lack of data but only lack of information is encountered. It is mainly used for encountering data which can be used for decision making, strategy and proper kind of planning[10]. A single kind of patient aims to be generated which is required for thousands of data elements. It is required for proper kind of diagnosis, medication and results in lab in results and its billing. It is mainly required for validating, integration into large source of given data which is helpful for proper kind of analysis. By analyzing all the given aspects that are point where the data is stored and scope of big data challenges has come into picture. This is only a small portion of healthcare.
Healthcare has slowed down the redesign the whole process which is due to adaptation of large number of technologies[11]. It can easily create huge amount of impact on certain number of areas like care delivery and lastly research. The healthcare technology is mainly inclusive of vast region of technology and compilation related to it. The biggest obstacle which is encountered is all about use of big data which is due to nature of healthcare information. Various research centers and another institute which come up with their own data[12]. It is considered to be very much difficult for integration which is because of concern related to privacy and data. It is well understood for various kind of standard which helps in underlying data. It is mainly noticed due to lack of metadata.
The whole healthcare system can easily make use of benefits which can be gathered from big data system. Various researchers can easily identify various opportunities by which they can collaborate and contribute. Cloud helps in easily identifying and analyzing the big data technology in much effective way[13].
However, there is certain number of technologies tend to exists. A proper process can be considered to be helpful in facilitating and accessing automate access which is encountered due to complexity and challenges. Providers patient and another kind of interest parties like researchers aim to provide access to securing access to data. It is mainly used for securing the data access to group. Big data technology can be easy for analyzing different patterns and irregulating. It can be easily used for prevention of any kind of threat and other types of fraud related to it.
Conclusion
From the above pages, it can be concluded that the essay deals with contribution of big data technology in Healthcare. In the above pages, various opportunities and challenges in Big data technology have been discussed in details. For successful implementation of big data technology and identification of big data solution, healthcare organization should focus on two kind of resources that is time and resource. It can provide the foundation which is required for stronger execution.
With the help of preparation, various organization will not be able understand various kind of benefits of big data technology. It will ultimately risk various kind of benefits of given big data technology along with various kind of risk in competitors. There is large number of recommendations for healthcare organization like building business intelligent center which is required for excellence along with focus on big data. A proper kind of access can be done on various kind of big data initiatives which is required to be developed for meeting all the corporate objectives.
References
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[1] Kambatla, Karthik, Giorgos Kollias, Vipin Kumar, and Ananth Grama. “Trends in big data analytics.” Journal of Parallel and Distributed Computing 74, no. 7 (2014): 2561-2573.
[2] Luo, Jake, Min Wu, Deepika Gopukumar, and Yiqing Zhao. “Big data application in biomedical research and health care: a literature review.” Biomedical informatics insights 8 (2016): BII-S31559.
[3] Chen, Min, Yujun Ma, Jeungeun Song, Chin-Feng Lai, and Bin Hu. “Smart clothing: Connecting human with clouds and big data for sustainable health monitoring.” Mobile Networks and Applications 21, no. 5 (2016): 825-845.
[4] Manogaran, Gunasekaran, Ramachandran Varatharajan, Daphne Lopez, Priyan Malarvizhi Kumar, Revathi Sundarasekar, and Chandu Thota. “A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system.” Future Generation Computer Systems 82 (2018): 375-387.
[5] Raghupathi, Wullianallur, and Viju Raghupathi. “Big data analytics in healthcare: promise and potential.” Health information science and systems 2, no. 1 (2014): 3.
[6] Viceconti, Marco, Peter J. Hunter, and Rod D. Hose. “Big data, big knowledge: big data for personalized healthcare.” IEEE J. Biomedical and Health Informatics 19, no. 4 (2015): 1209-1215.
[7] Wang, Yichuan, LeeAnn Kung, and Terry Anthony Byrd. “Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations.” Technological Forecasting and Social Change 126 (2018): 3-13.
[8] Weber, Griffin M., Kenneth D. Mandl, and Isaac S. Kohane. “Finding the missing link for big biomedical data.” Jama 311, no. 24 (2014): 2479-2480.
[9] Zhang, Yin, Meikang Qiu, Chun-Wei Tsai, Mohammad Mehedi Hassan, and Atif Alamri. “Health-CPS: Healthcare cyber-physical system assisted by cloud and big data.” IEEE Systems Journal 11, no. 1 (2017): 88-95.
[10] Luo, Jake, Min Wu, Deepika Gopukumar, and Yiqing Zhao. “Big data application in biomedical research and health care: a literature review.” Biomedical informatics insights 8 (2016): BII-S31559.
[11] Manogaran, Gunasekaran, Ramachandran Varatharajan, Daphne Lopez, Priyan Malarvizhi Kumar, Revathi Sundarasekar, and Chandu Thota. “A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system.” Future Generation Computer Systems 82 (2018): 375-387.
[12] Raghupathi, Wullianallur, and Viju Raghupathi. “Big data analytics in healthcare: promise and potential.” Health information science and systems 2, no. 1 (2014): 3.
[13] Viceconti, Marco, Peter J. Hunter, and Rod D. Hose. “Big data, big knowledge: big data for personalized healthcare.” IEEE J. Biomedical and Health Informatics 19, no. 4 (2015): 1209-1215.
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