The National Institutes of Health (NIH) and University of Mississippi Medical Center (UMMC) have teamed up to create what they hope will be the world’s largest health information dataset. What is the purpose of the dataset? To take some of the guesswork out of modern medicine.

As things currently stand, healthcare providers and patients are often left to try numerous treatments and strategies to see if they can find something that helps. If they eventually do land on the appropriate treatment, it is almost always the result of trial and error.

The leaders of the joint NIH and UMMC project are thoroughly convinced that big data can make a difference. By collecting and analyzing data on more than one million Americans, they hope to be able to produce comprehensive information that makes diagnosis, treatment, and prognosis more accurate and efficient.

Asking Meaningful Questions

For the record, the database for the joint project has been dubbed All of Us. It is structured to ask meaningful questions about participant health. Through targeted questions and answers, scientists hope to learn more about how genetics impact more serious health issues. Meanwhile, they should be able to crunch data in such a way as to provide a more targeted approach to the most common health conditions in America – like hypertension, for example.

Although it is not clear what constitutes a meaningful question, the point is well understood. We can compare the concept to our own healthcare datasets. All our data is directly sourced from the people it pertains to. Not only that, participants whose data we include have voluntarily provided that data.

Let’s say a healthcare worker looking for a new job is one of the job board websites owned by our parent company. That site asks the person to provide personal phone number and email if they do not want to be contacted at work. Furnishing that information indicates the person would rather be contacted through private channels.

Requesting personal email and phone number is a meaningful question. It proposes to the user a way to guarantee all contacts are made outside of the workplace. Entering such information is an indication of that person’s communication preferences.

Understanding Sickness and Disease

The same concept of asking meaningful questions can be applied to improving healthcare delivery. Researchers who know what to ask can utilize the answers to targeted questions to understand why people get sick. Answers to those meaningful questions can help researchers understand risk factors, recognize trends, and utilize predictive analysis to assess a patient’s long-term health.

None of this would be possible without the implementation of big data. Back when big data was first proposed, there were plenty of skeptics that believed developing the concept was a waste of time. But that was a long time ago. Today, big data is invaluable.

If the NIH and UMMC succeed in building the dataset they are shooting for, they will have access to a ton of data they can crunch for any number of purposes. The healthcare datasets they could produce from their research could potentially be staggering. And it is all being done in an attempt to help Western medicine better diagnose, treat, and cure disease.

Gathering healthcare data on more than one million volunteer patients is an incredibly vast undertaking. But once the data is in the system, the crunching can begin. It will be fascinating to see what the project produces a couple of years from now. Who knows? They could eventually come up with a digital system for projecting a person’s health trajectory for their entire lives.

Disclaimer: The viewpoint expressed in this article is the opinion of the author and is not necessarily the viewpoint of the owners or employees at Healthcare Staffing Innovations, LLC.