Introduction
Big data analytics for cutting costs
To develop a healthcare system based on big data that can exchange big data and provides us with trustworthy, timely, and meaningful information, we need to overcome every challenge mentioned above. Overcoming these challenges would require investment
in terms of time, funding, and commitment. However, like other technological advances, the success of these ambitious steps would apparently ease the present burdens on healthcare especially in terms of costs. It is believed that the implementation
of big data analytics by healthcare organizations might lead to a saving of over 25% in annual costs in the coming years. Better diagnosis and disease predictions by big data analytics can enable cost reduction by decreasing the hospital readmission
rate. The healthcare firms do not understand the variables responsible for readmissions well enough. It would be easier for healthcare organizations to improve their protocols for dealing with patients and prevent readmission by determining these
relationships well. Big data analytics can also help in optimizing staffing, forecasting operating room demands, streamlining patient care, and improving the pharmaceutical supply chain. All of these factors will lead to an ultimate reduction in the
healthcare costs by the organizations.