Big Data in the Health Sector

Big Data can help to evaluate information in health. Analytical approaches so far been associated mainly with technologies such as data warehousing and BI. Two related informative articles are What is Big Data and Big Data in the Cloud. The findings with various tools have helped many companies to implement or find out what their respective client expects and what they likes less for their business strategies.

Big Data is driven by manufacturers such as EMC, HP or IBM, who want to occupy this segment of the market – on the other hand promises the analysis to be faster and less costly. In the health sector in particular, IBM so far come forward with initiatives. In U.S., is a bit ahead on this IT field, The Institute for Health Technology Transformation recently did a research on Big Data published in the health industry. The study has also been supported by numerous professionals from hospitals and other medical institutions.

Big Data in the Health Sector : Challenges for Big Data

After an introduction part, the study that explains basically what is Big Data is and should be the aim, the authors challenge that are at least five sectors which are associated with this technology :

1. Collected information from web and social media sources (Facebook, Twitter, LinkedIn, blogs, health plans, websites and apps for smart phones);
2. Machine-to-machine data, information from sensors, meters or other instruments – particularly interesting in the medical environment;
3. Data from large transactions such as health bills or other receipts, receipts, invoices or accounting documents, which are frequently present in semi-or unstructured;
4. Biometric data such as fingerprints, genetic information, handwritten records, X-ray records, medical images, pulse, blood pressure, and similar information;
5. Un-structured or semi-structured documents such as KIS data, physician notes, e-mails or other information captured on paper.

The predominant types of documents in the health sector would be so far excellent for big data analysis, while classic BI analysis are mainly based on structured data from databases such as Oracle, DB2, or other. The study lists numerous examples in which Big Data analyzes have been carried out successfully.

Big Data in the Health Sector : Challenges for Big Data

The challenges begins to study the counts within the insufficient medical institutions to quickly make their documents available. These are either present in fragmented, hidden form and it takes a dedicated team to prepare them at all for analysis. There are therefore similar input difficulties as with classical data warehouse or BI solutions in which the data must be processed or often converted into readable formats.

In addition, partly due to the government health reforms in various countries, today much more data are generated as it was a few years ago. This “data deluge” to tame, bring into manageable forms, for many IT departments are hardly possible. Connection to external service providers would turn on their expertise. Hospitals and other institutions have such a developed and modern IT infrastructure them only in exceptional cases, so that at any time all necessary big data tools have prepared. So it would make investments in the server and storage systems required for any analytical data accesses can be performed. Data protection and privacy regulations are not clear. The question comes to what extent patient data is ever appropriate or released, to allow to reuse by Analytics? What happens when they are outside, in the extreme in cloud environments? Who is liable in case of damage? Pharma Spam are known, Big Data in the Health Sector can be more dangerous than Pharma Spam.