Healthcare And Big Dat Transformation Of Healthcare Sector

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

Healthcare stakeholders know how to value what they have captured and they have come up with many ideas to help with their goal. “Big data could transform the healthcare sector, but the industry must undergo fundamental changes before stakeholders can capture its full value” (Kayyali, B., Knott, D., Van Kuiken, S., 2013). Since the affordable care act has been in place there has been an increase number of patients seeking preventative care or even seeking help for chronic illnesses that they weren’t seen for because of lack of insurance. Because of that, there has been a shortage of physicians, nurses and other healthcare providers. So the stakeholders have another challenge on their hands in trying to hire more doctors and nurses to help with the increase of patients.

After I read “The Challenge: Moyen Sante Medical Sente, Chapter 7,” I learned how big data and data warehouses had caused a positive impact on health informatics. These impacts have reduced hospital readmissions, which has been a big setback for hospitals and healthcare organizations. The analytics system has caused health care systems to transform their health care system as they improve their information technology. Moreover, this may help advance the awareness of practitioner’s psychological decisions making especially towards data sources. As Ana and Ima showed a sign of agreement regarding the improve of their MSMC healthcare system in the future, Sarah provided a short video that intended to help answer the questions they were seek, such

With changes due to Healthcare Reform, healthcare organization’s are becoming more competitive in its market as they move towards finding the right effective fit through process improvements for their organization based on quality measurements, operational effectiveness, and financial performance in an effort to maximize their reimbursements in order to protect their margin and stay afloat in the healthcare industry to deliver the most profound care to the patient’s (Amerinet, n.d). Through new organizational architect and design, training, dashboards that helps to make matrix decisions, and big data analytics gathered from the electronic health record system, healthcare organization’s are driven to use the best fit resources and tools to improve their performance and be sustainable and successful in the healthcare market (Amerinet, n.d) (Stichler, 2017).

Electronic Medical Record (EMR) and Electronic Health Record (EHR) have revolutionized how healthcare is practiced in the past several years. HITECH Act of 2009 began to incentivize health care providers for using EHRs, to promote higher-quality and more efficient care. As the transition to electronic information occurs, the need for big data analysis and security have increased significantly in healthcare. EHRs implementation will aid researchers to utilize health data more efficiently as most of information will be easily accessible compared to traditional health record system. This allows researchers to spend less time collecting data and analyzing data much easier.1

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.

Thanks to Health information records and electronic medical records, there isn’t a doctor’s visit that information from typical demographic information to diagnosis information is discreetly collected in order to be able to run reports later. These reports can be used to pull a list of patients due for certain vaccines, adherence to medications, the medications themselves, diagnosis, BMIs, etc., the possibilities are really endless. According to Phillips, Population Health Management is the aggregation of patient data across multiple health information technology resources, the analysis of that data into a single, actionable patient record, and the actions through which care providers can improve both clinical and financial outcomes. What makes population health management successful is how informed clinical decisions can be made based off the information gathered by this aggregation of data. It also provides the platform for leaders to merge data analytics with clinical care primary care-led workforces. Risk stratification allows community workforces to extend care through patient engagement and community integration.

When we talk about healthcare data then it is maintained from long time. One of the reason healthcare providers maintained this data was due to compliance to law. This availability of data, which is seen as major positive for Big Data technology, has a limitation that it is protected by complex web of laws which make it difficult to access. It is like you have to unravel all the riddles posted by law before you can get to that data. For example in United States there is federal law Health Insurance Portability and Accountability Act (HIPAA) to protect healthcare data. This federal law already brought majority of healthcare data under its umbrella from 1996 onwards. It states that not only clinical information but demographic and financial

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 .

One of the new catchwords in healthcare is “Big Data”. Big Data is commonly defined by the three V’s, volume, velocity, and variety of data (Adamson, n.d., para. 4). I believe Big Data will live up to the hype surrounding it in healthcare. Even though it may take a while for healthcare to understand it and harness what it can do. Cultivating copious amounts of health data from a variety of sources has immense potential for everyone including the patient, healthcare organizations, and research.

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.

The American Bar Association (ABA) states that Big Data is the next revolution for health care operations. Health care costs are rising among both insurers, organizations, consumers and the government. Everyone wants to increase speed and efficiency without sacrificing quality of care. Health care organizations are now using Big Data, analytical tools and business intelligence to identify opportunities to reduce costs, boost efficiency and increase quality.

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 the new and still relatively misunderstood phenomenon in which companies are you using vast amounts of collected data to reveal patterns and certain trends within their collected data. Though big data is being used in a variety of different fields from retail to governmental uses, it is becoming most prominent within the healthcare field. Everyday thousands of people are admitted into hospitals and seen at various emergency clinics around the world. What if all this data from each individual seen at these clinics and hospital could be accumulated and a detailed report given to see signs of new diseases or new trends of medications effects? This is where big data is becoming such an integral part within the healthcare field.