As we know that Bigdata describes large volumes of complex, high velocity and variable data which require advanced technology to capture, store and analysis of information.
Big data is big and is even growing bigger in health care, U.S. health care data alone reached 150 Exabyte’s, which is equal to 30 times of all the words ever spoken by mankind. At this rate all the data will reach even more higher number. It is true that Bigdata has a wide range of impact on the American industry but the massive information sharing and analysis need to create remarkable benefits within health care. If we found out the main uses of Bigdata, we can observe that there are no better uses than that of healthcare. If we note the main need of health care sector is: how to secure, share and lower the cost. So, it is important for the health sector to get the tools, techniques and the infrastructure to use Bigdata effectively, which will in fact improve the quality of service, help them saving millions of dollars and sustain in the market.
How exactly does Bigdata work in healthcare?
Big data is a collection of large volumes of data generated from various tools such as:
- Social media like Facebook, Twitter, blogs which also include websites, health plans and insurance.
- Health care records, billing records and other unstructured formats.
- Information from scanners readings, meters and other sensors and machines
- Bio metric data such as medical images, finger prints, X-rays, MRI reports, DNA reports, retinal scans and other medical related information.
- Manually generated information like emails, prescriptions, medical appointments, rough notes on patient conditions etc.,
By digitalizing, formatting and effectively using Bigdata, health care sector and the related organizations will attain good benefits, which include detecting diseases at earlier stages, improving the quality and efficiency of healthcare, treating diseases successfully as they are detected at earlier stages, detecting health care fraud, it will help the government to manage specific disease effected populations.
Electronic health records in association with new analytics tools, open the door to mining information for the most effective outcomes across large populations.
The success testimonials:
There are some early success stories which show us the advantages and ease of work they could experience by using the Bigdata in health care solutions.
- Harvard medical school and Harvard pilgrim healthcare centre showed the potential for computer algorithms to analyse HER data to detect and differentiate patients with diabetes, the algorithms were successful in detecting the type I and II diabetes and also could identify patients who had been clinically diagnosed with diabetes.
- WHO (World health organisation) has initiated Bigdata in global health such that most of the middle and low income countries can experience the benefits and also helps the major health organisations to offer a better service in these countries.
- University of Ontario’s partnered with IBM to combine Bigdata platforms to develop Project Artemis, which help in streaming analytics to monitor the new born, surprisingly the hospital was able to discover the symptoms of nosocomial infections 24 hours prior.
Many health institutions in united states were able to use Bigdata and were able to gain the advantages in detecting health issues and infections and specific population health care solutions, and delivered healthcare effectively.
Strategies to perform Bigdata effectively:
- Simple and understandable tools: We need to create simple and understandable tools for the organisations such as dashboards, dropdowns such that they can access the information in ease and they can perform their real time operations and update the data for future references and prospects. The updated data will be used further for further detection of illness and will help in analytics.
Frame work: Creation of a frame work to analyse the whole data is very important part of the whole process, this includes designing models, techniques, use of tools, minimizing the cost, decision making, risk management, improvements according to the growing competition and other requirements.
- Improve the quality in all surroundings: Good health care transformation requires dramatic and sustainable changes to the structure and process of health care. The Bigdata team should work with the whole health care community for the improvement which together can provide a frame work that drives the administrative changes for achieving desired improvements to health care outcomes and efficiency.
- Fraud detection: Fraud detection is a very essential part of using Bigdata, the Bigdata techniques are used to detect fraudulent claims, errors in payments, reviewing all the free service treatments. Previously all the medical claims were checked manually but with Bigdata, fraud detection is made easy, it will let the people know about the costly treatments, procedures and will help them in overcoming delays and will help in cost reduction.
BIGDATA also can be used to improve endeavours such as population health management and will help in treatment for a wide range of chronic conditions.
Hence using Bigdata will help in a rapid development in health care industry and also help in fraud detection and a very advantageous format of health care for people and also to the health sector.
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Motivitylabs is a U.S(Texas) based mobile, cloud and Bigdata insights solution provider with a global presence. We look forward to create applications using next generation technology.
Motivitylabs was incorporated in 2010 and has quickly risen to 138 position on the Inc. 5000 by successfully executing projects including development and testing efforts for some of the largest software companies in the world along with many Start-up companies.