History of big data and barriers exist for using big data in health care today

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History of big data and barriers exist for using big data in health care today

A number of use cases in health care are well suitable for a big data solution. Some academic health care institutions are making experiments with big data or utilizing it in improved research projects.

A general history of big data in health care

In 2001, Doug Laney coined the terminology “the 3 V’s” in order to explain the concept of big data. The 3 V’s are volume, velocity and variety. However, other analysts supposed that this is too simple, and there are more things to think about when defining big data.
In health care, we do have large volumes of data coming in. Most of that data is gathered for recreational purposes. However, neither the volume nor the velocity of data in health care is truly high enough to require big data these days. Therefore, the vast majority of the data collection in health care today could be considered recreational.

Barriers for utilizing big data in health care nowadays

Lots of challenges with big data have to be solved in the current big data distributions. Two barriers to the general use of big data in health care are the technical expertise required to use it and a lack of integrated security surrounding it.
In terms of expertise, the value of big data in health care today is largely restricted to research due to the fact that using big data requires a very specialized skill suite. Hospital IT experts familiar with SQL programming languages as well as traditional databases are not well prepared for the steep learning curve and other complications surrounding big data.

In fact, most organizations require data scientists to manipulate as well get data out of a big data environment. These are usually Ph.D.-level thinkers with significant expertise, and typically, they are not just floating around an average health system. As a result, these experts are difficult to come by and rather expensive, and only research institutions usually have access to them.
The good news is, with the help of new tooling, people with less-specialized skill sets will be capable of working with big data more easily in the future. Big data is coming to embrace SQL for querying. And as soon as this happens, it will become useful in a health system setting.

Regarding to security, in health care, HIPAA compliance is non-negotiable. Nothing is more necessary than the privacy as well as the security of patient data. However, there are not many good ways to manage security of patient data.
Health care organizations can take some steps today to guarantee better security of big data. Big data operates on open source technology with inconsistent security technology. In order to avoid big problems, organizations had better be selective about big data providers and avoid assuming that any big data distribution they choose will be secure. The best choice for health care organizations is to purchase a well-supported distribution rather than beginning with a raw Apache distribution.

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