What Is Big Data

Our world Is becoming an increasingly digital space today. We manage, share and store our lives. Online data is gathered from our devices, computers and smartphones that collect and transmit information on what we do, but that is just the beginning soon. This phenomenon is transforming our understanding of the world and our place in it. It’s become known as big data. Big Data could be invaluable for business. It could provide a window into the lives of customers that we have never previously imagined,

Big data in healthcare

Today’s vast amount of medical data needs to be integrated and access to intelligently to support better health care delivery.

Big Data made smart can create new networks of knowledge sharing. By measuring and monitoring processes digitally, we can compare data more easily. Such insights facilitate streamlined workflows, greater efficiencies and improved patient care. Systematic analysis of extensive data can help to detect patterns so that clinicians can tailor treatment to individuals and project health outcomes.

Digital networks can bring together partners and knowledge sharing, delivering context relevant clinical information at the point of care enables more holistic decision making.

Healthcare can benefit from big data when it is made structured, relevant, smart, and accessible. analyzing the data gathered across your community can allow you to identify groups or individuals who are at risk for certain diseases or who may benefit from proactive lifestyle changes. by comparing clinical outcomes across various populations and demographics. You can discover evidence on the effectiveness of different treatment options which can be used to create more effective targeted treatment plans for individual patients.

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How big is big data

To give an idea of how big big data is Consider this, the amount of data created in the world from the beginning of coming up through and including the 2005 is now created every 2 days. Every health care alone is estimated data volumes globally have reached 150 exabytes. That’s equivalent to $150 million terabytes in size and it’s growing at a rate of two exabytes per year. This explosion of data is creating new opportunities to not only save money through more efficient use of information, but also to analyze broad population health data to discover new trends which can lead to more informed clinical decisions and improved outcomes.

5 V’ s of Big Data

• Volume: which is the amount of data that is collected and stored.
•  Velocity: The speed at which data is generated and accessed.
• Variety: refers to the wide array of data sources and formats.
• Veracity: the variability of data structured and quality.
•  Value: arguably the most important thing, which is how you can get the most out of your data.

How it works

More data generated means more data to process, analyze, and store. This can make predicting and future data volumes difficult, especially when looking outside traditional ology departments (radiology, Cardiology etc.) leading to a lot of guesswork in assumptions when determining initial system requirement. Most traditional systems are vertically scalable, which means the system hardware must be replaced when growth exceeds capacity. This leads to new capital expenditures, migration cost and system downtime, which can become quite expensive. What is needed is a system that is horizontally scalable with horizontal scalability. Additional hardware and software entities can be added on an as needed basis to accommodate growth in real time.

All Nodes in a data center work together as a single logical unit. As new systems are added, they automatically become part of the cluster, and data is immediately distributed and load balance across all nodes, which can exist in a single data centers or be distributed across multiple physical locations. This unique architecture provides native high availability and disaster recovery, ensuring business continuity for your healthcare organization. The Reltio platform is hardware and storage agnostic, allowing you to utilize the affordable standard commodity hardware.

In fact, new physical hardware may not even be required as Rialto nodes can be fully virtualized, allowing you to leverage existing infrastructure. There is no need for costly migration activities or lost productivity due to system downtime. simple yet scalable design saves you money by simplifying overall system administration and significantly reducing capital and operational costs. Emerging trends in the areas of healthcare and its benefits Digitalization of the health records:

•  Easing work flow: Electronic Health records are less time consuming also would require less maintenance.
•  To lower health care cost- outpatient care cost will be reduced.
•  Enhancement of patient care
•  Improvement of public health

Cloud and Big data benefits:

• Safer and better data storing
•  Big data access is improved
•  Cost of health care reduction
•  Epidemic prediction
• Improving quality of care and efficiency
• Development of new treatments and drugs

Information and communication technology benefits:

• Reduction of patient waiting time
•  Better access for the rural areas
• Enhanced efficiency which leads to savings

High tech surgical procedures:

• For example, robotic surgery where the physician can do surgical procedure by means of precise tools attached to a robotic limb.

Benefits includes:

•  Lesser proportion of complications
• A lesser amount of blood loss
•  Smaller hospital stays
• A reduced amount of discomfort
•  Enhanced quality of life afterwards of surgery
•  Small openings which means minimal scarring

Future of big data in Healthcare The biggest medical systems in the future need not require going to hospitals. It’s going to be devices that are monitoring the lives of millions of patients simultaneously. That’s looking to see, do you have the beginning signs of a cancer emerging to not treat the cancer, but to prevent the cancer from ever occurring . Big Data’s impact on the practice of medicine fundamentally can transform the physician’s ability to personalize care directly for you and the way we’re going to get that. As you have a handheld device that has amazing capability, can bluetooth enabled the inhalers for asthma patients, scales, blood pressure monitors, EKG devices.

We can to have individualized models for each person that maps out their health course trajectory. It will be something that you’re engaged in on a daily basis, but not necessarily actively. You’re just being triggered if you need to be because the algorithm says, okay, you’re at super high risk and the next year progressing into type two diabetes, but if you can catch that before the catastrophic state, then the person’s not having to come into hospital.

The data has to be more accessible. The ultimate end game is you have this personalized therapy specifically tuned to who you know you are, the stuff that’s going on inside of you. If a physician can know that they can better serve the patient, better serve the health system it and it benefits everybody.

Challenges for Big Data

Now a days patients are taking an increased interest in their healthcare searching for their own care providers at a variety of institutions, data that is gathered, comes from a collection of traditional and nontraditional sources and exist in a wide array of formats such as X-ray scans, Physician reports, and notes, or even data from monitors or wearable technologies. Together, this data is creating a flood of new health information. Each piece of information is an individual piece in the puzzle which together forms a picture of the patient’s overall health. Unfortunately, this data is sadly underutilized due to challenges in data access and format.

Data is often fragmented across multiple individual systems, making it inaccessible outside of the institution in which it was acquired, leaving physicians in the dark regarding potentially relevant history which may exist for their patient. Variances in data formats need to interoperability problems between systems. Physicians often need to log into multiple different systems, each with different credentials in order to gain access to bits and pieces of the patient record. When systems and data or isolated like this, caregivers did not have all of the information they required in order to make informed clinical decisions, which in turn can lead to unnecessary duplicate tests, delays in diagnosis and treatment, and ultimately suboptimal patient care.

Solutions

The solution is a patient centric, cross-enterprise, content-agnostic data warehouse, which allows healthcare communities to share and access patient data regardless of its source or format. Advanced connectivity tools which provide a patient centric view of your data will allow you to discover, aggregate, and normalize patient records from anywhere across your community. When combined with a universal viewer capable of displaying a wide variety of data formats, physicians will be able to diagnose patients using a single application at any time from anywhere. Selecting a system which adheres to the latest industry standards in profiles for interoperability such as DIACOM, HL 7, and IHE will allow you to seamlessly integrate IT solutions and share data across the enterprise. Finally, the solution should be content agnostic so that data is always stored in its native format and nothing is ever altered or wrapped so that any department contributing to a patient’s care can also contribute to their clinical record. By distilling information from across your healthcare community, you can create a single integrated, actionable patient record providing caregivers with relevant clinical history at the point of care, and most importantly, delivering timely quality cost effective care for patients.