Predictive analytics and Personalized Healthcare

The healthcare system is undergoing revolutionary changes with plenty of challenges to meet with the use of new and existing sources of data to deliver personalized care. Clinicians are required to not only make decisions about healthcare but incorporate volumes of health data generated and controlled by patients. Integrating the data into healthcare enables stakeholders to make better decisions, which is made possible with predictive analytics software.

The multiple benefits of predictive analytics

There are numerous benefits of implementing a predictive analytics solution, which include the ability to provide better patient care and significant reduction of costs. While the thought that healthcare could be reduced to algorithms may be intimidating, the reality is that predictive analytics is very promising with the ability to deliver accurate results. Predictive analytics is something doctors have been doing on a large scale for a long time. However, predictive analytics software it a step further and helps to better collate and measure previous data that was hard to obtain.

Combining data with existing sciences of clinical medicine enables a better understanding of the relationship between external factors and various aspects of human biology and medicine. This results in improved ability to deliver personalized care.

The role of historical data

A predictive analytics solution is the best way to allow patient care to be personalized for each individual by studying historical data. It helps physicians make better clinical decisions and avoid adverse events. These solutions like Jvion's RevEgis are designed to reduce readmission rates and help in chronic disease management and patient matching. The objective is to treat individual patient better by widening the data set.