The Estimation Of Big Data Examination Of Medicinal Services

As defined by the magazine, CQ Researcher, big data is the collection and analysis of enormous amounts of information by supercomputers (CQ Researcher, 1). This collection and analysis has led to many great feats in the fields physics, medicine, social

Big Data can help in a range of steps included in clinical trials such as patient profiling so as to identify the right candidates through analytics of demographic information and historical data, assessing medication availability, surveying past clinical trial events, intervention for appropriate drug dosage, and remote patient monitoring. Moreover, it helps recognize the possible adverse and undesirable effects of a new drug even before they are

Clinical decision making is a complicated process that depends on human capability to provide full attention to memorize, and create enormous amounts of data to all areas. IT systems are able to access information, arrange them, and recognize links between them. Clinicians often ‘know’ information such as a patient’s allergies, drug interaction and if that drug is on recall.

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

The role of knowledge base in a Clinical Decision Support System is to reduce medical errors and provide the best quality healthcare available. Knowledge base refers to the practice of medicine based on the best available scientific evidence (JAMIA). Knowledgebase continues to expand and it is crucial in developing clinical decision support systems by encoding concepts coming from experts in the field to provide a way to analyze the data and generate expert advice. With a knowledgebase system in place healthcare providers will have a more focused diagnosis of the disease and the treatment that will need to take

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

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

In recent years, there has been an increasing use of electronic health records (EHR) in the healthcare industry. Historically, EHRs were merely used for monitoring the progress of patients [1, 2] in most cases. However, according to PubMed [3], since 2005, a lot of work is going on in building of prediction models on EHR data. As EHR systems are quite large in size and contain variety of historical data, they are ideal candidates to study Big Data issues,

Big data is challenging and changing healthcare systems very quickly. In order to keep up with all the new technologies and continue improving health, it is very important to know how to maintain the momentum of this movement. It is necessary to have cross-sector imperatives and strategies to help stakeholders reach their goals [4]. Here are some cross-sector imperatives that are most important to be followed:

Big data plays a vital role in healthcare organizations which helps to predict the disease of the patient. As the world’s population is increasing and the models of treatment delivery are changing rapidly, the datasets of the patient also keeps on increasing. In order to maintain these large number of patient’s medical records, big data helps to maintain these records which reduces the cost. The specific information is extracted from the data rich environment and produce the information about the history of the disease and how it can be cured. It is done by using the decision support system implementation for health care with the use of software that aids in the process of decision-making in order to ensure the correct diagnosis of any illness

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.

Data in the healthcare industry can include patient demographics, financial information or clinical documentation. Management of this data can include storing in a file, file server, an email, an electronic healthcare system or other locations. Therefore, Data Management is the process of managing how the data collected and how it is stored so that it can be used efficiently and effectively in the future.

The promise of data-driven decision-making is now being recognized broadly, and there is growing enthusiasm for the notion of ``Big Data.’’ While the promise of Big Data is real -- for example, it is estimated that Google alone contributed 54 billion dollars to the US economy in 2009 -- there is currently a wide gap between its potential and its realization.

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”.