Big Data Analytics for Prediction Modelling in Healthcare Databases

Bigdata in healthcare has manifested as well as benefited healthcare practioners and scientists around the globe to detect hidden patterns for future clinical decision making. The major complexity faced in real world application domain is the volume of Electronic Health Records (EHR) which has gathered due to high end IT based technology which has boomed in past century for early detection of disease. The traditional technology tools adopted were incapable to discover hidden patterns due to its computational requirements. So, Big data has its generosity need in healthcare intervene technology due to diverse nature of data and accelerated speed of data that needs to processed for better diagnostic interventions. This study has been conducted using predictive data analytics on big data for discovery of knowledge for future decision making. The study consists of information about 3,56,507 patients from 1982–2010. Data curation has been done by organizing under various categories including Age, Year (1982–2010), Incidence Counts (1982–2010, all age groups and both genders), and Mortality Counts (1982–2010, all age groups). The results represents invariable patterns which can be utilized for future predictive modelling.