When it comes to big data, just about every industry can benefit in some way or another. The healthcare sector is just starting to realize the potential value of big data, and the next several years will illustrate just how powerful and useful it can be to have detailed records of all kinds of patients over time.

The healthcare industry has been known to periodically incorporate trending technical best practices to cut costs and save lives. The creation of websites with a strong emphasis on userability has been a recent push, and by extension the application of stronger network performance monitoring software, free or paid. Hospitals and individual clinics are leveraging an overall digital approach to record-keeping and storage. These technical optimizations made within the healthcare industry have primed the way for greater advancement within the new field of big data.

The idea of collecting and analyzing as much customer information as possible has now become a major goal in the most cutting-edge marketing departments. It lets the company understand exactly how consumers behave and what attract them to the brand, reducing the costs of acquiring and retaining customers. However, the healthcare industry is new to the concept of big data. It is only recently that care providers have been legally obligated to start switching over to electronic medical records. That has opened the door to storing all of that data for useful analysis and potential cost-saving measures.

One of the most difficult aspects of health care is that each patient responds to treatment in different ways. As a result, it can be a long, expensive, and dangerous process to find exactly the right treatment for any combination of patient and condition. Skipping some or all of this trial and error period to find a useful intervention right from the start would save a lot of time and money, while also reducing the risk to the patient. That is what some researchers are doing right now—developing tools that clinicians can use to build personalized treatments. It might sound like it would be more expensive to tailor treatments to fit each patient, but in reality, the opposite is true.

For example, one team of researchers built a tool that would let doctors put in the characteristics of a patient with pulmonary nodules, and then the tool would search the world's largest database of cases of those nodules and come up with some matching cases for comparison. This lets the doctor see what worked and what didn't work in those similar cases.

The potential savings from tapping into personal data in this way are quite large. A report from McKinsey had a ballpark estimate of twelve to fifteen percent cuts in the cost of administering care. Considering the amount of money that America spends on healthcare each year, that is huge. It is also important to note that the coming wave of retiring boomers will lead to a higher level of health care expenditures. That means it is even more important to start finding ways to cut costs now, before it gets out of control.

The potential savings do not only come from personalized medicine. There is also the area of genetic testing, which is a different kind of big data. Researchers are already aware of some genetic markers that are associated with an increased risk of developing particular forms of cancer or other diseases. Right now, the information does not have a great deal of predictive power, but as more people get their genomes sequenced and as healthcare providers track the outcomes of those people, we might see a better picture emerge, where genes can predict a lot about the most important health risks each person faces.

While it does raise privacy concerns, proper information security and network monitor investment will go a long way towards protecting patient data from anyone who wants to steal it. The cost savings that the industry could experience are so large that it is hard to imagine care providers not trying to tap into big data in some way.