The Fear and Hope Behind Data in Healthcare

Big data in Healthcare

Until recent years, data storage in healthcare has taken up lots of space and untold amounts of paper. Big data and digital data storage in healthcare may seem like the solution to those hidebound practices of old. Patient information and other data can be stored securely on a server where it’s accessible at all times and doesn’t take up office space with physical documents.

Some experts claim that big data is the solution to many problems facing the medical community, while others argue that it is hurting the healthcare industry. What causes this fear and hope behind data in healthcare, and who will turn out to be the ones on the right side of medical history?

Hope for the Future

Big data has provided a unique tool for data-heavy sciences like genetics. A single human genome, depending on how it’s sequenced, can take up multiple terabytes of storage space. Sorting through all of the data on an individual human genome can be difficult, if not impossible, for a single researcher or even a team of researchers.

That is one of the most advantageous applications of big data to date — using machine learning algorithms to examine collected data much faster than a human ever could. These programs can even be used to find patterns in the data that might otherwise elude human researchers and do so much faster than a team of researchers alone could ever manage. Machine learning and automation aren’t just good for examining data but when used to input data as well these technologies can reduce errors, labor costs and long-term risks of data entry errors.

This data use occurs even in everyday medical practices. Research has found that the average hospital is generating more than 650 terabytes of data every single year — the majority of which is patient information, test results and stored patient imagery.

One of the biggest goals of big data in medicine is to create a graphical database that represents all of the data that has been collected and will continue to be collected as medicine continues to become digitized in the future.

Changing the Face of Healthcare

Big data is already being used to change the face of healthcare for the better. By using remote monitoring and smartphone apps, medical professionals can help to predict and prevent some of the 2,000 cardiovascular deaths that happen every single day. New single lead EEG technology means that cardiac patients don’t have to be restricted to the hospital, giving doctors a better picture of their physical health and typical daily activity.

We’ve already spoken briefly about predictive algorithms and machine learning. In addition to being used to help us sort out things like the human genome, it can also be used to predict things like disease outbreaks and who might be susceptible to various medical conditions — as long as it has enough information, that is. The more data a system has, the more accurate its predictions can become.

These predictions alone could help save money and reduce healthcare costs — experts have found that in the United States healthcare system alone, more than 1/3 of the industry’s resources are spent on wasteful resources and inefficient care.  When put in numbers, this accounts for upwards of $750 billion every year. By applying predictive analytics to individual health care, the care that each patient receives is improved, reducing waste and improving overall patient outcome

Healthcare Disruptions

Not everyone in the medical industry is a fan of big data. We’ve got smart everything — everyone has a smartphone in their pocket, and many people are starting to incorporate smart technology into their homes and businesses. While this might not be a bad thing to some people, many who oppose the use of big data claim that it’s too much information. We have so much data that the relatively early-stage machine learning programs and predictive algorithms we have today can’t gather accurate insights from it. Once these tools develop more, this massive influx of data won’t be as big of a problem, but right now we’ve got hundreds of terabytes of data to store and not a lot of use for it.

The move toward big data is also leaving some older professionals behind. One doctor, in New London, New Hampshire, recently lost her license to practice medicine for refusing to use a computer in her practice.  The doctor in question, Anna Konopka, feels that ‘electronic medicine’ is destroying the human component of the doctor-patient relationship, but her refusal to utilize more modern techniques has cost her ability to practice medicine.

There is also the potential problem that accompanies all networked systems — the vulnerability to outside hacks. Just look at the WannaCry virus that all but crippled the NHS computer system earlier this year — one overlooked attachment allowed a Ransomware virus to infiltrate a large number of computers in medical facilities, compromising both patient privacy and patient care.

Big data is definitely here to stay, both in medicine and in other industries. It is clear that this technology has both pros and cons, but it is just beginning to show us the full extent of what we’ll be able to do with this sort of technology.

 

Bio: Nathan Sykes writes about trends in the tech industry for websites like Business Computing World and IT Chronicles. To read more from Nathan, check out his blog, Finding an Outlet.

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Kalyan Banga223 Posts

I am Kalyan Banga, a Post Graduate in Business Analytics from Indian Institute of Management (IIM) Calcutta, a premier management institute, ranked best B-School in Asia in FT Masters management global rankings. I have spent 14 years in field of Research & Analytics.

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