Analytics / Predictive Modeling
So many companies are just starting to get into big data that very few have gotten to the point where they need to find out how to use it. There will most likely never be a one-solution-fits-all. Simply trying to find more about predictive modeling using big data either leads to previous implementation examples or discussion in theory. Despite the lack of current resources in this matter, nearly everyone can see the value hiding within.
One of the leading necessities for predictive modeling is health care. Years before Health First was ready to collect big-data analytics on their patients, an attempt was made to sooner discover sepsis patients through standard reporting. The problem is that late-stage sepsis mortality rates can reach well over 30% depending on the hospital (luckily Health First never reached this figure). Doctors threw out every idea they could think of such as combinations of cultures, heart rate, oxygen level, blood pressure, temperature, admitting diagnosis, last doctor visit diagnosis, patterns of orders for previous patients with sepsis. Eventually a particular combination of these measures allowed an advanced notice for numerous patients thus saving lives.
This is, in essence, predictive modeling. The doctors needed a collection of all the possible data points to even attempt to solve a problem. They generated their own hypotheses to discover possible solutions and began testing them. After ridiculous amounts of testing and exceptional results, an automated solution was crafted. Currently at Health First, when particular vitals are combined with specific diagnoses, the hospital system is able to automatically create sepsis orders to treat patients sooner. Predictive modeling saved lives.
Not every company will save lives using predictive modeling and analytics. Even still, similar methods have been used to sooner discover fraudulent credit card usage and save the banks, along with their customers, a lot of money and time. Using the latest analytics and predictive modeling techniques and technologies, we can help you identify trends and put your data to work for you. If your servers are in a data center, in a cloud service, or don't exist yet, we can help architect the right plan for your business.