As early as toddlers, humans learn the word “big.” Small and little are used of child-size items, while adult-sized clothing, dishes, and furniture is said to be big. But just how big can we get? Physical items can only grow so large, but when “big” refers to something we can’t grasp or see, such as data collection, the size becomes seemingly infinite. It’s hard to track, impossible to stop, and requires non-stop efforts to sort out its millions of sections. Now that’s big.
This data can come from all corners of the world – the Internet, school classrooms, store statistics – the holders are almost as ongoing as the data themselves. But if this data is so absolutely huge, how do we track it?
Breaking Data Down
Within the medical field, big data comes in two forms – structured and unstructured. Structured data is that which can be found on a computer or database where it can be used in deciphering analytics. Unstructured data refers to doctor notes or patient charts that are handwritten/typed, but not yet entered into a system. There is some lag time with inputting this data – and combined with a growing number of patients and treatment options, the flow never stops.
Just how big is the data? Every year the amount of information in existence doubles, much of which is big data. As of last year, each day 2.5 quintillion (2.5X1018 ) bytes of data were created, bringing the grand total to well over 2 zettabytes (that’s over 2 billion terrabytes). Analyzing this info, however, can also provide a great deal of answers, especially in health care. Big data can help predict epidemics, allow doctors to compare symptoms with similar cases, provide more efficient patient care, and more. The benefits are almost as endless as the data themselves.
But without analyzing, it’s just data without a purpose.
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When data is big, so big that it never actually stops growing, how can we learn from its information? In theory the facts are helpful, pointed, and come from so many variables that practically no group has been undocumented. But when it comes to sorting it all out, where do we find a starting point? Thanks to analytics, software that tracks down the impossible, big data, hospitals are seeing the benefits of their tedious records.
But it’s not just information these analytics are compiling, it’s what to do about them. By crunching numbers, symptoms, and other probabilities, healthcare professionals could just see actionable results. For instance, if a patient has symptoms A and B and has been to the doctor four times in the past year, analytics could help predict a specific cause. It could also compare visit dates and compile which seasonal sicknesses each patient is susceptible to catching.
Perhaps the biggest benefit to this big data analytics is the lack of expense. While the data itself needs to be deciphered, there’s no outside research involved. Healthcare providers can gain access to hundreds of predictable diagnoses by using the data they already compile. Doctors can also help more patients while spending fewer resources and time on individual scenarios.
- Patients can expect better value from their healthcare
- Lowering the burden on state-funded programs
- Reducing the impact of staff shortages
- Increasing healthcare treatments and delivery
- Finding patterns among diseases and their effects
To date, 90 percent of the world’s data is unstructured. However, by analyzing these numbers, specifically those related to healthcare, there is much to be gained. Professionals can host better treatment options while spending less time and money, while patients will receive better options and value – a win-win situation to adjusting the public’s view of health.