Health CARE Prediction using Predictive Analytics

Abstract

Throughout the years, several studies have been conducted on how to improve the health sector’s management and administration activities, as well as, most importantly, the healthcare delivered to its patients. In the health-care system, data is currently growing at an exponential rate. In this view, the deployment of technology capable of utilizing it in a constructive way for the company, assisting it in achieving its goals, is critical. Health data analytics, particularly analytics that are used for making predictions are being used as a tool for enabling more preventive treatment alternatives. Despite having access to an abundance of data, even though there is no actionable knowledge using which healthcare industry can make predictions. This is due to the fact that, despite its abundance, healthcare data is fundamentally complex and fragmented. Critical care that is also a part of healthcare areas, also facing a problem of increasing population as well as economic pressures, due to which it is difficult for most of the human beings to get required treatments. When we talk ICU patients their health frequently changes at every movement. When in a county most of the population is aged then there will be more need of ICUs due to the health problems of old people. Equally, patient expectations are increasing with the advancement of technology in healthcare sector, but it is not possible to deliver the required service due to increasing inflation. Better, more productive care is thus the big challenge. This paper we are going to examine the use of predictive analytics in healthcare sector as well as how it is different than the other sectors where the predictive analytics are being used. It also has been also discussed in this paper the various applications of predictive analytics in healthcare sector and the challenges that predictive analytics are facing in the healthcare sector.