Use Of Big Data On Improving Patient And Health Related Outcomes

Worldwide use of computer technology in medicine began in the early 1950s with the rise of the computers. In 1949, Gustav Wagner established the first professional organization for informatics in Germany. Medical informatics research units began to appear during the 1970s in Poland and in the U.S. Since then the development of high-quality health informatics research, education and infrastructure has been a goal of the U.S. and the European Union. (NYU graduate training program, 2010) Changes in the healthcare environment produced fundamental shifts in the delivery of healthcare. The altering landscape of healthcare is creating a huge demand for health data analytics. The growth and maturity of healthcare informatics over the past decade has been a prime catalyst in positioning the healthcare industry for the changes posed by reform measures. By understanding the process of analytics, clinical informatics specialists say healthcare providers have the insight necessary to make the process adjustments in the future.(Riskin, 2013)

Medicine in the 21st Century has continued to push the boundaries of science to unthinkable limits, often fusing complex technological elements and concepts together to achieve great feats. Two major contributing factors that have increased the use of high-technology in modern day medicine are Evidence-based Medicine and Health-Informatics. One study completed at Ohio State University (2016) proved how beneficial combining high-technologies such as Health Informatics Tools (HIT) and Evidence-Based Medicine can be. "Achieving a vision of 'interventional informatics ' will requires us to re-think how we study HIT tools in order to generate the necessary evidence-base that can support and justify their use as a primary means of improving the human condition" (Embi et al, 2016). This synergistic effect is just one of many countless examples of the successful advancements in medicine today. These strings of successful advancements in medicine can almost certainly be linked to the progression of specific

In recent years, there has been a growing interest in the application of biomedical informatics in many aspects of the healthcare system. This is due to an increasing recognition that a stronger healthcare information system is crucial to achieve a higher quality care at lower costs1. Biomedical informatics is defined as “the scientific field that deals with biomedical data, information and knowledge-their storage, retrieval, and optimal use for problem solving and decision making.”2Biomedical informatics plays significant roles in the healthcare system and it has been applied in various ways in the healthcare system, specifically in the aspect of health care information system such as electronic medical record (EMR), personal health record (PHR), computerized provider order entry (CPOE) systems, bar-coding medication administration systems, telemedicine, telehealth, and administrative information systems 2.

This report outlines how data from EHR can be used towards Meaningful Use (MU), Big Data Analysis, Machine Learning and Advanced Computing for better healthcare decision making process. Will try to understand EHR’s ability to integrate with other systems and tools for data sharing/mining and how this is transforming into better care management. Health Information Technology for Economic and Clinical Health (HITECH) MU EHR incentive program have provided the much needed “push” towards adoption of EHR and resulted into incentivized payment for providers which is contributing towards increased quality, safety and efficiency within health care organizations (HCOs)[1]. Future is now revolving around how EHR can contribute towards latest data driven technological advancements in healthcare and contribute towards better care management with reduced cost.

The advent of the Electronic Health Record is ushering in a new era in advanced healthcare. The next 20 years will be an exciting time to be involved in health care as a Health Information Manager. Analyzing the myriad of health information which could reveal astonishing medical breakthroughs excites my imagination. I see the perfect pathway for my future. I am on track to graduate with Honors from Portland Community College’s Health Information Management Program in June 2016.

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 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.

The nation collects volumes of health information, however much of the data remain siloed and difficult to compile. These healthcare big data siloes are making it difficult for insurers, providers, pharmacies and others to truly work together to coordinate care (Clough, 2016). Furthermore, these stakeholders are inhibiting coordinated care through their prevention of using real world data for decision making. Consequently, each patient must still take control of their healthcare and provide physicians, pharmacists, healthcare facilities, and other stakeholders with updated information on their situation, visits, and

Hospitals will probably use big data to analyze the prescribing practices of individual technicians. It will help determine who is over or under prescribing. This will have an impact on the quality and safety of patient care as well as consumption costs.

It could consist of patient-related data, data from healthcare devices like monitors and sensors, hospital records, application data measuring health metrics and everything including social media posts, webpages, emergency correspondence, research data from genomics to innovative drugs, advertisement data, newsfeeds and articles in medical journals. As much as there is scope for finding out patterns among these data, it is not easy to implement predictive analytics in healthcare industry because of the limitations like hand-written prescriptions, scanned images and medical records which comprise of unstructured and disintegrated data. Moreover, medical data is involved with legal and privacy issues. The adoption rate of analytics in healthcare industry is quite slow making it more challenging.

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 mining is the process that companies and businesses use to interpret raw data and turn it into useful information. This is achieved by using software that serves this purpose. Although the term "data mining" is a newer one, the concept has been around for over two decades. This technology allows users, healthcare businesses and the like, to analyze data from many angles in order to categorize it and summarize key identifiable information. This has become especially important in the healthcare field, since electronic health records (EHRs) have become a standard in patient care. Although it brings some privacy concerns to surface due to the massive amount of patient data shared through the data mining process, it is also seen as a very successful and helpful tool in more ways than one. Like in other businesses, data mining may be used in healthcare to asses and improve satisfaction and to help detect fraud and abuse. For example, when data mining is used to address patient satisfaction, this should help the staff recognize patterns, patient preferences and patient expectations in order to be able to further meet their current and future needs. At the same time, this technology also allows for the establishment of what is considered a normal pattern, like when filing insurance claims. The system would then recognize anything that doesn't fall into these normal patterns and may help reduce fraud and abuse.

Big data in health care has seen improvement in the quality of care as well as efficiency and productivity. In the area of improvement of quality of care, we can see that

Healthcare is rapidly evolving and applying new innovations into its field. It now includes more concepts that combine both information and technology, for example, the area of health information technology (HIT). Health information technology is also known as health informatics and includes the different areas of clinical specialties or diseases, user, agent, technology, and information level (Martin-Sanchez, Maojo, & Lopez-Campos, 2002). The field of bioinformatics fits into the category of health information technology because it is a disciplinary field that involves both science/ health and technology (Hoyt, 2010).

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”.