Data Mining And Its Impact On Healthcare

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

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.

Hunt, D.L. and Haynes, R.B. et al. 1998. Effects of computer based clinical decision support

They used facts and arguments from various sources, such as studies and authors. As they are introducing the topic, they use the ideas of Lev Manovich to justify their argument that the name “Big Data” can be misleading. Manovich observed that Big Data has been used to refer to data sets large enough to require supercomputers, yet large amounts of data can now be analyzed on much simpler computers. Boyd and Crawford contend that the value of the industry does not simply come from the large data sets, but the “patterns that can be derived by making connections between pieces of data…” By relating Manovich’s idea, their argument made more sense. As computers become more advanced, bigger data sets look much simpler. But the connections Big Data makes are still valuable, no matter how advanced computers

One key concern for policy makers, regulators, care givers and patients is healthcare quality (Harnett, 2016). Quality problems are reflected in a variety of ways for the use of healthcare services, the underuse and overuse of some services, and misuse of others. Waste and inefficiencies have negatively affected the healthcare system. Improving the quality of healthcare and reducing medical errors is a priority for many organizations that regulate the healthcare industry. Many are looking for the highest quality of care they can get, as quickly as they need it. Lots of attention has been placed on the healthcare quality improvement by payers, clinicians and consumers. There is a big interest in patient outcomes and safety, care coordination, efficiency, and cost cutting. Healthcare is more vital to people than most other goods or services, and we have a strong collective interest in assuring that the healthcare system works as well as it can. The consequences of poor quality can be dire. Another reason is that people spend a lot on healthcare and these costs continue to rise. Scores of provider quality measures have been developed by accreditation organizations, regulators, payers, and healthcare providers themselves to measure specific areas of practice and performance. Measuring the quality of healthcare is important because it tells how the health system is performing and leads to improved care (Uyar &

The value of Clinical Decision Support Systems is having additional avenues monitoring patient’s data input. The Clinical Decision Support Systems are offering notifications of patient’s record data to specified department or medical personal.

In the reading I noted that The Institute of Medicine(IOM), found that patients were not satisfied with the quality of care that they received (Joel, 2013) I feel that the healthcare services for a patient should be that not only of a good quality but it should be cost effective, and make improvements for better outcomes with their overall health We have many organizations out there like NQF, NCQA, and TJC to help us with achieving this goal and maintaining a better quality of health with our patients and their needs.

One of the foremost concerns faced by hospital and healthcare set ups today, is that of the increasing discrepancy between the amount of data created and the data that is actually understood and consumed. According to a survey carried out by Frost & Sullivan, nearly 1 billion terabytes (and counting), of data is held by hospitals and medical centers. This data is estimated to grow more than 40 times over the decade. The need for Data intelligence is no longer a stand by thought. Organizations are facing a growing pressure to become more efficient in the way they store, utilize and share medical/healthcare data.

Health Data Management help their subscribers focus on the most important issues and topics in the news such as revenue cycle analytics and accountable-care models, electronic health record platforms and data storage, telemedicine and mobile applications.

Big data is a term to describe the 2.5 quintillion bytes of data that we create each day. There are many ways that the big data is collected and used; some types may be good, and some might not. As we read the book “Too Big to Ignore” by Phil Simon, you will see this is a controversial debate inside of the book. The book talks about whether big data collection is good, such as data mining or bulk data collection. In the story, it tended to lean towards the side of agreeing with the use of data collection.

On the example of quality and value being the major goals in the healthcare system, the key drivers and root causes for the change are the current low quality and high costs associated with our current healthcare system. Despite having higher costs than the rest of the industrialized world, our outcomes are not better (Squires & Anderson, 2015). While this likely has many social and socioeconomic contributors such as lifestyle choices, poverty, and the way in which our healthcare system developed, there is still great deal of the costs and negative outcomes that are associated with poor quality, medical errors, and the system not fully adapting best practices. There are a few root causes for these individual issues as well as I will briefly

In my opinion with technology developing constantly data mining holds great potential for the healthcare industry to enable health systems to systematically use data and analytics to identify inefficiencies and best practices that improve care and reduce costs. It has been proven by some experts that the opportunities to improve care and reduce costs concurrently could apply to as much as 30% of overall healthcare spending. This could be a win/win overall. But due to the complexity of healthcare and a slower rate of technology adoption, our industry lags behind these others in implementing effective data mining and analytic strategies so in conclusion data mining will continually be a great asset to the health care industries .

Big data and its definition has changed over the years. In a 2011 research project by MGI and Mckinsey’s Business’ defined big data as

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.

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”.