The healthcare industry records a staggering amount of data. As healthcare providers continue to transform the delivery system to focus more on outcomes and value -- and less on volume -- harnessing the power of that hospitals and health systems using analytics to improve care across whole communities, for instance.

The notion of big data -- analyzing extremely large sets of diverse data for improved performance -- has been popular in other parts of the economy for a while. Parts of the healthcare community are at the nascent stage embracing the concept.,

What Sets Big Data Apart from Regular Data?

Thanks to our increasingly digital lives, our actions can be more closely scrutinized than ever as we leave more electronic bread crumbs behind. However, putting big data to good use is incredibly challenging, often requiring specialized analytical tools and software and highly trained analysts, and this is especially true in healthcare where data must be used to make critical decisions about patient care.

The datasets being collected today are so large that they become very difficult to store, let alone analyze. It's not as simple as just looking at a graph and noticing that a trend is going up; in big data, there are often many different trends and interactions involved.

Most of the standard statistical tests were designed to handle small sets of data taken from large populations, and they just aren't effective when it comes to big data. Running these traditional tests on big data can lead to false conclusions, and some believe that this poses a significant problem for science as a whole.

This is the basic challenge facing the healthcare industry today. How do we organize and analyze this data to come up with real insights about our health?

Big Data and Healthcare

The growing use of big data in medicine is not only a good idea, it's vital to meet the needs of our evolving system. Increasingly, providers are being reimbursed for the value of the services they provide -- outcomes -- versus the traditional payment model that focused on volume. For instance, big data can help providers develop more effective care management plans for patients with chronic conditions. But the healthcare industry has some unique obstacles to overcome when it comes to big data, in addition to the basic problem of how to manage it.

First, a lot of medical information is separated (or “siloed”) because the hospitals, clinics, and other providers that collect the data don't typically share it with each other. This has created a situation where data may be stored in many different locations and formats, which can make the data very difficult or even impossible to combine.

A second challenge is individual privacy, which is always a major concern in healthcare. Identity theft in general has been a growing problem for some time, with Social Security numbers and credit card information being the well-known targets of thieves. But now medical records are becoming an increasingly desirable target on the black market, and this type of information is reportedly up to ten times more valuable than credit card data.

Companies are Tapping into Big Data

There are certainly obstacles to using big data in healthcare, however, several organizations have taken up the challenge with the goal of analyzing it to come up with practical applications for disease prevention and furthering better treatment outcomes.

The Pittsburgh Health Data Alliance, for example, is a collaboration between the University of Pittsburgh, the University of Pittsburgh Medical Center, and Carnegie Mellon University. They use machine learning techniques to analyze health data, and want to create new technologies to reduce the cost of healthcare.

In a different vein, a company called Express Scripts has been leveraging big data for years to be more accurate and efficient. Express Scripts, which fulfills pharmacy prescriptions, uses the data they collect to predict who is more likely to stop taking their prescriptions. They can then take certain steps to help prevent this, like sending letters or auto-refilling prescriptions.

These are just two examples, but there are many other organizations working to utilize big data to improve care. By learning how to analyze and understand this data, we can gain powerful insights that will help improve patient outcomes, reduce preventable errors, and provide a better standard of care.

A fundamental requirement that can serve to anchor individual healthcare data is a national patient identification (NPID) solution. An NPID solution will be instrumental in helping to meet the challenge of matching patients correctly to

their records across the care continuum as the volume of healthcare data continues to grow exponentially. Without a patient identification solution, the use of big data in healthcare will not be maximized to its full potential.Big data and medicine are coming together in new and exciting ways. We are asking for your help with the CHIME National Patient ID Challenge, whose goal is to create a national patient identification system to provide safer, more effective, and more efficient healthcare system for all. You could win $1,000,000!