Big Data and the Future of Nursing

Big data, particularly as it relates to something as personal as one's health is something of an uncomfortable topic for many people. You don’t want to think of your information floating out there somewhere in an invisible “cloud,” available for anyone to look at and analyze. 

Fortunately, many of the most significant fears pertaining to big data are overstated and misinformed. Most data is anonymous, used by healthcare professionals not to learn more about you, but to identify patterns within a population and adjust their care accordingly. 

In this article, we look at how this technology is shaping the way that nurses do their jobs 

What is Data Processing?

Data processing or analysis is all about looking at what happened in the past, identifying a pattern, and making reasonable assumptions about how that pattern will play out in the future. In the context of healthcare, this is often used to determine patient outcomes, and even anticipate future surges.

A very straightforward example of this is the concept of “flu season.” Of course, flu germs don’t have a calendar hanging around somewhere. “Oh, my. Winter already?” You can get the flu at any time of the year.

However, through data analysis, health advisors are able to look at when the flu has been the most prominent in the past, and make reasonable assumptions about how prominent it will be in the future. Using this information, they can brace communities for what is to come, helping them to potentially stave off the worst of the flu’s impact. 

This not only means advocating for vaccines but specific vaccines that are best positioned to protect one from the viral strain that is currently in rotation. 

Similar methods are used in Covid prevention. Data can’t prevent viral outbreaks from taking place, but it can be used to cushion the blow.

Narrowing Medical Possibilities

Of course, nurses are always interested in achieving the best possible outcome for their patients. Data helps to narrow their focus, cutting through the vast ocean of possible medical outcomes to narrow possibilities down to a manageable number. 

There are currently algorithms that can be used to provide quick diagnosis possibilities for medical professionals (in most states, doctors, not nurses are the ones who need to formally produce the diagnosis, though this isn’t the case everywhere). 

Instead of pulling out a dusty book and navigating through dozens of possibilities using (here’s an old word for you) the index, you get an instant list of three or four possibilities. 

This speeds up the diagnosis which subsequently vastly improves the healthcare system's ability to provide swift care. 

Understanding Disease

Data also helps healthcare providers like nurses understand the nature of specific diseases. Using big data, they can understand what combination of risk factors alter the likelihood of medical problems. It’s an enormous amount of information, but it narrows to the individual. 

This patient is diabetic, and they have high blood pressure. Knowing this, the best course of treatment is….And so on. 

Better Patient Outcomes

Naturally, all of this accumulates into better nursing. Improved patient outcomes that wouldn’t be possible without data. Patients do better because nurses have more specific options when it comes to developing a care plan.

This translates not only into more success in treating major conditions, but also an increased ability to prevent those conditions from developing into a serious state in the first place. As data technology proliferates, this will lead to a significant increase in future hospital resources. Better preventative care translates into less medical stress in the future. It’s a simple, but highly effective dynamic that has the potential to shape the future of healthcare.

A Future without Nurses?

Does it sound crazy? Technology has automated so many jobs that were once thought essential. Drivers, cashiers, line workers, even surgeons….

Robotics combined with advanced AI algorithms have created machines that can perform many of the same surgical maneuvers once only possible at the hands of a human. These machines can even use GPS-oriented technology to make positioning and cust that are optimal for the specific person’s dimensions. 

This has resulted in smaller cuts and therefore quicker recovery times. Right now, these devices are operated by surgeons, who subsequently still do some of the physical work. However, it’s not so difficult to imagine a future in which many mainstream surgeries lack the human elements that have been deemed essential since the dawn of medicine. 

Can the Same Be True of Nursing?

Probably not. Nursing work depends on a combination of complicated skills. There is, of course, a knowledge-based component of the process that machines can replicate and enhance. However, so much of the bedside nurse’s job is of an impalpable but essential nature. 

They provide a level of emotional support that few if any other positions in the world of healthcare come close to matching. Nurses will continue to have work even as big data continues to proliferate in the healthcare industry.

What we may see, however, is more nurses trained specifically to work with data. Data processing in the nursing profession is currently out there. Many nurses, particularly those in leadership positions, use it every day to plan out how resources will be used, and make strategies for better patient care. 

We’re not quite to the point where you can’t graduate nursing school without a firm understanding of digital technology, but it is fair to say that Big Data is firmly, unalterably on track to become a significant component of healthcare in the years to come. Undoubtedly, this will change the way that nurses do their jobs, but the effects will stretch far beyond that, touching all corners of healthcare.