How Big Data is Quietly Fighting Diseases and Illness

            This article discusses the effects that Big Data has on the medical field presently. Its narrows in on three major illnesses that have recently been the most popular in foreign countries, such as Ebola, Sepsis, and Polio. The article further explains how having the information that Big Data supplies on these three diseases has helped discontinued spreading the disease from the places in which it already exists.

                The first main point that this article makes is the effect of Big Data with the widely known disease, Ebola. Ebola was one of the largest outbreaks that occurred in 2014.  Big Data, specifically from mobile mapping, was essential to discover the geographical locations which helped determine where to send the relief teams. This mapping was used in two distinct ways: the first was by tracking population movement patterns, and the second was documenting cases where Ebola had occurred (http://dataconomy.com/how-big-data-is-quietly-fighting-diseases-and-illnesses/). “In disaster zones, real-time analytics that process and churn huge amounts of data can help pinpoint previously unanticipated trends, limit the number of deaths and, in doing so, massively reduce the spread of disease.( http://www.cnbc.com/2014/10/01/how-big-data-could-help-stop-the-ebola-outbreakcommentary.html)” With the help of Big Data, numerous lives were saved and hopefully many more will be too.

                The second point that should be observed from this article is Big Data’s effect on Sepsis. This illness is also known as “blood poising” and has a high mortality rate.  This disease shuts down one’s organs resulting death, and the main reason why the mortality rate is high is because the symptoms are extremely difficult to catch until it is too late. Amara Health Analytics worked with a big data repository and created a predicative model that collects data from bedside monitors. “Simply by hooking these machines to a cloud-based system, they replaced the fuzzy, traditional methods of diagnosis with accurate, evidence-based and detail-oriented analysis ( http://dataconomy.com/how-big-data-is-quietly-fighting-diseases-and-illnesses/)”. By having the information in almost real time, medical professionals have the ability to stop the illness from progressing.

                The final point is how big data helps healthcare. As exemplified above, big data can help fight and eradicate diseases, but it can also help the healthcare system in a broader sense. The organization WHO hopes with the use of Big Data, the anti-vaccination movement will disappear. The hope is Big Data will be able to change the conversation for those who support the anti-vaccination movement (http://dataconomy.com/how-big-data-is-quietly-fighting-diseases-and-illnesses/).  Another article says prevention is better than a cure. Big Data, specifically through apps, has helped many people lower their risks such as lowering chances of heart issues by tracking how many steps one takes (http://www.forbes.com/sites/bernardmarr/2015/04/21/how-big-data-is-changing-healthcare/#3267bcf232d9). These apps demonstrate how people are more aware of their health; therefore, changing the conversation which will potentially move more people towards vaccinations.

             A point that I believe the article overlooked is potential malfunctions the apps, and devices could have, which could potentially cause a medical professional to make incorrect decisions. This can lead to the data being loss all together, or producing incorrect results.