Big Data Healthcare Linked to Predictive Medicine

As technological advances are happening for every industry, the need to keep up is essential. This is the same within and maybe even more so for the healthcare industry. We’ve all heard news reports about a new technique practiced in an operating room, or a new device that helps to take precise images of the body. But, that isn’t where the true power of technology is being felt in healthcare; behind the scenes lies the power of information. Specifically Big Data in healthcare.

Big Data is a term that has been around for a couple of decades but has more recently come into its own. Initially Big Data was described as a large amount of data – whether structured, semi-structured or unstructured – that could be mined for information. As you might guess, this is quite ambiguous and highly interpretive. Questions arise like:

  • How much data is considered Big Data?
  • What is considered structured, semi or unstructured data?
  • How do you mine for information?
  • What kind of information is produced?

Over time, more details have been nailed down, especially in relation to Big Data in healthcare. The terms that best describe what is going on are:

    Volume – sometimes in the realm of peta- and exabytes
    Velocity – fast and furious
    Variety – structured and unstructured
    Variability – variety of different sources
    Veracity – ability to be accurate and verifiable
    Complexity – not the same form or order each time

How does all of this relate to Predictive Medicine and Care? Although far from simple, the basic fact is that with the collected information received and then mined for patterns and trends, it is possible to predict reoccurring issues that could be handled before patient’s care becomes more critical. This isn’t anything new, in fact, many businesses have applied this concept to predict future purchases, recommend products and services and create loyalty programs to benefit customers.
As human beings, we fall into health patterns based on internal and external conditions or circumstances. We may like to think that we are all unique, but we are more likely to be quite similar when physicians are looking at overall patient health, chronic disease diagnoses, and hospital admissions/readmissions. This is accomplished by comparing other patients with comparable ailments and applying a predictive algorithm, which interprets and associates like situations.

This may all seem self-evident, but some of these patterns and population health trends are not such. There are some visible predictions that can be made, such as when there is an outbreak of chicken pox at an elementary school, it will have a peak and then taper off. Same with other common viruses in known circumstances. However, having an outbreak of chronic heart failures isn’t possible due to the fact that this isn’t contagious, but some of the same signs may be visible if a physician is able to understand a patient’s medical history and compare it to other individuals who experienced similar physical markers and dispositions. By intervening before diseases and illnesses are at a chronic or dyer stage, both patient and physician usually have more options available and the ability to come out the other side with a better result.

Big Data in healthcare provides the insight to not only utilize the power of stored and analyzed data from countless others, but also to have real-time data available to work from. This enables a physician to take into account current patient sitting in their clinic and understand possible afflictions or illnesses that may be on the horizon. More accurate and personalized care can then be administered.

Predictive healthcare and health management cannot happen without a foundation of established Big Data. Big Data has the capability of providing predictive analytics for patient care, along with other hospital and clinic efficiency in processes and procedures. These last items afford a more cost effective and precise administration of treatment for both patient and professional. The true full potential from healthcare Big Data has yet to be tapped. But, it is by applying the known capabilities, plotting out high-efficiency goals, and seeking for more advances needed within the organization can Big Data begin to serve higher purposes. Big Data in healthcare and Predictive medicines and treatments are inextricably connected and have a long future ahead of them.