How Social Media and Big Data Aid Healthcare?

The rate of technological progression over the past few decades has been astounding, so much so that computing technology is finding it tough to keep up with Moore’s Law. Gordon E. Moore, in 1965, made a rough calculation that the number of transistors that a chip holds will double every two years, thanks to consistent demand for progressively advanced products. We are now at a point where standard silicon-technology-based chips are finding it tough to cram themselves with additional transistors. So while the advent of better forms of chip-making emerge, the point is clear that we’ve come a long way in a very short time. This only makes it logical that healthcare, one of the essential industries for mankind, uses what’s at the forefront of the technology of its generation. On top of the list for this generation is the barrage of social media data we put out into the world.

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Tweeting for Better Health

In May 2011, researchers from the University of Iowa figured out a way to use Twitter to track diseases in terms of their level of reach and activity in the U.S. The studies were conducted during the influenza A H1N1 pandemic. The published report shows that the team of three scientists was able to successfully use Twitter to check the developments in public sentiment during the spread of swine flu. In addition to this, they also managed to measure the level of activity of the disease through tweets from different regions. The report conclusively showed that social media platforms, especially Twitter, can be easily used to track public concerns over health and thus gauge the spread of diseases.

And the Twitter train doesn’t stop at contagious diseases and pandemics, either. In early 2015, University of Pennsylvania researchers stated that they can correlate region-based data on heart disease to a higher rate of negative Tweets. The researchers compared the data published by the CDC and the general emotional quotient of tweets from various regions. They found that there was a direct proportion between the number of emotionally negative tweets and the prevalence of coronary heart diseases. Of course, we need to remember that correlation does not imply causation – just because one sends negative Tweets does not mean they have heart disease. But it is data like this that can lead to a more concrete analysis for a better healthcare structure.

Big Data and Predictive Healthcare

The global healthcare industry is taking its next big step already: healthcare is on its way to becoming more proactive than reactive. What this means is the incorporation of intuitive technology that will anticipate patient problems before they happen, based on previously collected data. While this could practically spell out miracles for patients, we are still a long way from creating the perfect predictive healthcare system. But as a starting point, we have the currently trending big data business.

Big data can work better with healthcare to make it more intuitive. For instance, the piles of data gathered from one person regarding his/her eating habits, workout routines or lack of exercise, and sleeping habits, can be vital in telling whether that person is susceptible to diseases or not. With big data analytics, this can be performed efficiently for a large population. The health records can even span across generations of a family, enabling medical knowledge of genetic traits that might show up in new generations.

There are many other tech trends that can be extremely helpful in the field of medicine; many of them already are: improved sensory tech and better materials are being used in performing delicate surgeries and creating state-of-the-art prosthetics. Doctors all over the world are making the most out of the Internet and high-speed data transmission to create live global lecture halls where veterans perform surgeries in their OR while the others watch on their screens and learn. Indeed, we have come a long way from non-sterilized amputations and witch doctors, and into concepts that, ironically, seem more and more like magic.