The role of big data in medicine is one where the healthcare industry can build better health profiles and better predictive models around individual patients so that we can better diagnose and treat disease. This is one of the main reasons why Medical Big Data is very crucial now in the age of technology.
One of the main limitations of medicine today and in the pharmaceutical industry is our understanding of the biology of disease. Medical big data comes into play around aggregating more and more information around multiple scales for what constitutes a disease—from the DNA, proteins, and metabolites to cells, tissues, organs, organisms, and ecosystems. Those are the scales of the biology that we need to be modeling by integrating big data. If we do that, the models will evolve, the models will build, and they will be more predictive for given individuals.
Physician engagement also plays a big role in the advancement of medical big data in the healthcare industry. One of the biggest challenges facing Medical Big Data in healthcare is not data or software or data scientists, but getting doctors to enter their documentation. If a physician does not document notes in real time after seeing patient then you won’t get the information on the patient in real time.
It’s not going to be a discrete event—that all of a sudden we go from not using big data in medicine to using big data in medicine. It is more of a continuum, more of an evolution. As physicians begin to build these data models and aggregating big data, they will also start to test and apply these models to individuals, assessing the outcomes, refining the models, and so on. Questions will become easier to answer. The modeling becomes more informed as they start pulling in all of this information.
The medical field and healthcare industry are not the first to encounter big data. There have information-power companies like Google and Amazon, Netflix and Facebook, and a lot of the algorithms that are applied there to predict what kind of movie you like to watch or what kind of foods you like to buy. Most of them use the same machine-learning techniques. Those same types of methods, the infrastructure for managing the data, can all be applied in medicine using medical big data.
The concept refers to vast quantities of data created by the mass adoption of the Internet and digitization of all sorts of information, including health records too large or complex for traditional technology to make sense of. New big data technologies, however, hold promise for consolidating and analyzing these digital treasure troves in order to discover trends and make predictions.
According to advanced and experienced physicians, one of the most exciting implications for big data in healthcare is that providers will be able to deliver much more precise and personalized care. With a more complete, detailed picture of patients and populations, they’ll be able to determine how a particular patient will respond to a specific treatment, or even identify patients at risk before a health issue arises. That being said, as of right now, most health systems can do plenty today without big data. The many things they can do – including meeting most of their analytics and reporting needs. There are many physicians who prefer to be more grounded in ambition when it comes to the use of big data. They argue that the healthcare industry hasn’t even come close to stretching the limits of what healthcare analytics can accomplish with traditional relational databases—and so, therefore, using these databases effectively is a more valuable focus than worrying about big data.