Why Is Big Data Important In Healthcare

The company is a medical reimbursement company that deals with patients’ personal information from social security, to medical history and banking information. As technology in the healthcare field continues to expand, we have begun to use more big data to store all our patient personal health records and our employees’ personal records. Maintenance and processing of various and high volume data have created the “Big Data” challenge. As Gartner (2015) said: “Big Data is high-volume, -velocity and -variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making” [6]. Under the Health Insurance Portability and Accountable Act (HIPAA) laws, the healthcare industry is privy and held to a very high standard to protect and keep all patients’ personal information private, safe and secured; Digitalization and accumulation large healthcare data provides great potential for healthcare data. The key to the best patient-centric, evidence-base and accountability care is delivered through big data in healthcare (Yang, Li, Wang, Chen, Wu, Wang, Pan and Mulder 2015). There are still many healthcare challenges that need to be addressed to help enhance healthcare services. With cloud computing in healthcare, the company is one step closer to lowering their operational cost and eliminating the use of hardware and software to store data. With all the company’s data stored on networks, servers and applications it makes it easier for the data to be accessible any part of the world. Some of the advantages of cloud computing includes availability, performance and load balancing (Malekabadi, Javan & Akbari 2015). When all of the company’s data is stored on the networks and computed, it is taken by Iron Mountain and stored in a remote location. With the continued growth of innovative technology cloud computing will continue to

1) Big Data in Health Care via EHR: - Big data in healthcare comprises of 4 major components: - a) Volume of Data b) Variety of Data c) Velocity of Data flow and d) Veracity of Data. Big Data represents the tools, processes and procedures

Researcher believe that the availability of big data will be of great impact especially in the medical field. They believe that when medical records are easily available to Doctors, doctors will be able to provide immediate diagnosis and medical treatment to their patients. Using this data is a great benefit to Doctors because they can look up prior successful treatment from other patients to help treat new patient. The challenge Doctors may encounter with so much information is that they may become overwhelmed and incorrectly delays treatment or not provide treatment to their patients. Also, the searchable information can be misleading or misunderstood by the medical provider and he or she based on the searchable information can incorrectly providing the same treatment to all the patient with the same

The concepts are the significant advancement in examination and access to quality information. The new aspect of big data that is essential for its application is the variety formats it receive data. The data streams in different format of structured and unstructured (Groves et al., 2016).The data comes in numeric database, videos, audios and email. The data also comes from multiple sources. It is therefore ease to detect the trend and nature of the information in the system. Data management is one of the key aspect of data mining. It involves examination of data and identification based on source and quality (Crockett, & Eliason, 2016). These elements create utility of the information in the system. The health care will therefore get quality information for improving its

Systems without a knowledge base, on the other hand, rely on machine learning to analyze clinical data. There are pros and cons to implementing clinical decision support systems. The foremost challenge is that a CDSS must be integrated with a healthcare organization 's clinical workflow, which is often already complex. Some clinical decision support systems are standalone products that lack interoperability with reporting and electronic health record (EHR) software. Furthermore, incorporating large amounts of data into existing systems places significant strain on application and infrastructure maintenance. CDSS is "a process for enhancing health-related decisions and actions with clinical knowledge and patient information to improve health and healthcare delivery.

The ability of companies, governments and healthcare to harness data is important to find hidden information about how things are working in their organization. These organizations can then decide how thing should work and how things might work better depending on management decisions. Companies and governments use big data to track and analyze processes and customers for profit and efficiency. In healthcare big data is analyzed to understand how effective treatments and facilities are and make necessary changes. The bigger the data set the more necessary it is to use proper analytic techniques, types of analytic techniques are descriptive, predictive and prescriptive.

In the United States, health care price information is rarely made available to the health care consumer when they receive the service. Patients are usually become aware of the costs when they receive the bill. The price health care can vary radically by health care provider. Furthermore, prices can even vary by payer for the same provider. According to one study, consumers paid 10 to 17 percent less when they were given access to comparative price data. This tended to work best for consumers who had to pay for at least a portion of their care out of pocket. According to a paper that was published in the American Economic Journal: Economic Policy, when patients had access to price data and were willing to shop around, they could be paying significantly less for everything from routine screenings to knee surgery \cite{www-google-transparent}. This tended to work best for consumers who had to pay for at least some portion of their own care.

In the field of public health the concept of bid data is defined as utilizing large scale information from different sources to understand the outcome of an outbreak or disease. According to Khoury and Ioannidis (2014), the use of big data can help understand problems at a faster rate. For instance, epidemiologist are always working hard to identify which populations are more at risk and use credible internet sources and systematic reviews for information. As opposed to the earlier times of John Snow who took a longer time to understand the reasoning for the outbreak in London, big data is able to shortened the time and help reduce the prevalence of disease. Hence, improve the health outcomes of populations (Khoury and Ioannidis, 2014). A major priority in the field of public health is to based prevention programs based on evidence based research that possess statistically significant in the

The Clinical Decision Support Systems have challenges to overcome such as information technology must be design a effective system which notify certain outlier medical information data input. This requires a very through collaboration between the Information Technology Department and the medical facility. Once the specified notifications are designed the medical facility will perform a test run to confirm accuracies and promptness of the required notifications. The next challenge with Clinical Decision

Clinical Decision Support Systems (CDSS) support medical clinicians in making evidence-based decisions and diagnoses by providing scenario-pertinent information from patient data in the electronic

Clinical Decision Support Systems is a helpful and beneficial aid the healthcare industry decision making. Clinical Decision Support Systems is needed in majority of healthcare processes. The healthcare system is considered to be one of the largest industries in the United States. The services that healthcare providers provide are endless. The Clinical Decision Support Systems use tools and systems in order to determine different scenarios of how to explore the risk associated with different situations. There has been a large increase in the amount of technology that is used and there is higher need for decision making to be integrated in the healthcare operations.

Big data is an interesting concept, in which people use data to analyze trends, patterns, and associations and make use of these revelations to predict outcomes. You are using data every day that is being recorded to identify people’s desires and requests, and more specifically your desires and requests. Big data is used in retail, government, healthcare, car companies, and education, basically everywhere. Big data can allow for great advancements and prevention in all aspects of life, more specifically in healthcare. Big data is important to healthcare, because it can allow professionals to identify who has a greater risk of a disease and thus allows early detection and prevention. It allows tracking which medicine is more effective than the other. It allows for healthcare providers to have better records and accuracy in each and every patient. Big data is important to healthcare and here is why.

Informatics has affected many areas of the medical field. Informatics has improved the field by “helping people to revisualize and redesign their information management and knowledge management skills and learn new ways of using clinical data to mange clinical practice and patient care” (McLane & Turley, 2011). The purpose for this paper is to explore informatics in streamlining paperwork, provide decision support tools, and review contribution that is made towards patient safety.

As we know, for delivering good qualitative service in healthcare industry, data plays an important role. So it’s necessary to understand the fact that the big data must be used in a right way to make health service industries successful. For managing and analysing the big data it’s important to have a good knowledge about the healthcare data complexity, framework, technologies for “big data analytics in healthcare industries”.

Big data is an extensive collection of structured and unstructured data. It is a modern day technology which is applied to store, manage and analyze data that are not possible to manage, store and analyze by using the commonly used software or tools. Since all of our daily tasks are overtaken by the modern technologies and all the businesses and organizations are using internet system to operate, the production of data has increased significantly in past